Add GitHub ML run 20261001T173519000000Z-e6749d09
Browse files
coverage/20261001T173519000000Z-e6749d09.json
ADDED
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@@ -0,0 +1,2812 @@
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"query": "\"synthetic data\" in:description created:2024-01-01..2024-12-31",
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|
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"query": "\"neuroimaging machine learning\" in:readme created:2024-01-01..2024-12-31",
|
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"query_id": "medical.neuroimaging",
|
| 2800 |
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|
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}
|
data/observations/2026/10/01/20261001T173519000000Z-e6749d09.jsonl
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
state/historical-sample.json
CHANGED
|
@@ -2418,77 +2418,88 @@
|
|
| 2418 |
"query": "\"customer segmentation\" \"machine learning\" in:description,readme",
|
| 2419 |
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|
| 2420 |
2026,
|
| 2421 |
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2025
|
|
|
|
| 2422 |
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|
| 2423 |
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|
| 2424 |
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|
| 2425 |
"query": "\"machine learning\" cybersecurity in:description,readme",
|
| 2426 |
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|
| 2427 |
2026,
|
| 2428 |
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2025
|
|
|
|
| 2429 |
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|
| 2430 |
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|
| 2431 |
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|
| 2432 |
"query": "\"demand forecasting\" in:description",
|
| 2433 |
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|
| 2434 |
2026,
|
| 2435 |
-
2025
|
|
|
|
| 2436 |
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|
| 2437 |
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|
| 2438 |
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|
| 2439 |
"query": "\"dynamic pricing\" \"machine learning\" in:description,readme",
|
| 2440 |
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|
| 2441 |
2026,
|
| 2442 |
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2025
|
|
|
|
| 2443 |
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|
| 2444 |
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|
| 2445 |
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|
| 2446 |
"query": "\"ecological forecasting\" \"machine learning\" in:description,readme",
|
| 2447 |
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|
| 2448 |
2026,
|
| 2449 |
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2025
|
|
|
|
| 2450 |
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|
| 2451 |
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|
| 2452 |
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|
| 2453 |
"query": "\"educational data mining\" in:description,readme",
|
| 2454 |
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|
| 2455 |
2026,
|
| 2456 |
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2025
|
|
|
|
| 2457 |
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|
| 2458 |
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|
| 2459 |
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|
| 2460 |
"query": "\"load forecasting\" energy in:description,readme",
|
| 2461 |
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|
| 2462 |
2026,
|
| 2463 |
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2025
|
|
|
|
| 2464 |
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|
| 2465 |
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|
| 2466 |
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|
| 2467 |
"query": "\"fraud detection\" \"machine learning\" in:description,readme",
|
| 2468 |
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|
| 2469 |
2026,
|
| 2470 |
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2025
|
|
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|
| 2471 |
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|
| 2472 |
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|
| 2473 |
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|
| 2474 |
"query": "\"industrial defect detection\" \"deep learning\" in:description,readme",
|
| 2475 |
"years": [
|
| 2476 |
2026,
|
| 2477 |
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2025
|
|
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|
| 2478 |
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|
| 2479 |
},
|
| 2480 |
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|
| 2481 |
"query": "\"intrusion detection\" \"machine learning\" in:description,readme",
|
| 2482 |
"years": [
|
| 2483 |
2026,
|
| 2484 |
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2025
|
|
|
|
| 2485 |
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|
| 2486 |
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|
| 2487 |
"applied.inventory-optimization": {
|
| 2488 |
"query": "\"inventory optimization\" in:readme",
|
| 2489 |
"years": [
|
| 2490 |
2026,
|
| 2491 |
-
2025
|
|
|
|
| 2492 |
]
|
| 2493 |
},
|
| 2494 |
"applied.learning-to-rank": {
|
|
@@ -2895,77 +2906,88 @@
|
|
| 2895 |
"query": "\"microbiome\" \"machine learning\" in:description,readme",
|
| 2896 |
"years": [
|
| 2897 |
2026,
|
| 2898 |
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2025
|
|
|
|
| 2899 |
]
|
| 2900 |
},
|
| 2901 |
"bio.microscopy-cell-analysis": {
|
| 2902 |
"query": "\"cell segmentation\" microscopy in:description,readme",
|
| 2903 |
"years": [
|
| 2904 |
2026,
|
| 2905 |
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2025
|
|
|
|
| 2906 |
]
|
| 2907 |
},
|
| 2908 |
"bio.molecular-dynamics": {
|
| 2909 |
"query": "\"molecular dynamics\" in:description",
|
| 2910 |
"years": [
|
| 2911 |
2026,
|
| 2912 |
-
2025
|
|
|
|
| 2913 |
]
|
| 2914 |
},
|
| 2915 |
"bio.molecular-force-fields": {
|
| 2916 |
"query": "\"machine learning force field\" in:readme",
|
| 2917 |
"years": [
|
| 2918 |
2026,
|
| 2919 |
-
2025
|
|
|
|
| 2920 |
]
|
| 2921 |
},
|
| 2922 |
"bio.phylogenetics": {
|
| 2923 |
"query": "\"phylogenetics\" in:description",
|
| 2924 |
"years": [
|
| 2925 |
2026,
|
| 2926 |
-
2025
|
|
|
|
| 2927 |
]
|
| 2928 |
},
|
| 2929 |
"bio.protein-design": {
|
| 2930 |
"query": "\"protein design\" in:description",
|
| 2931 |
"years": [
|
| 2932 |
2026,
|
| 2933 |
-
2025
|
|
|
|
| 2934 |
]
|
| 2935 |
},
|
| 2936 |
"bio.protein-folding": {
|
| 2937 |
"query": "\"protein folding\" in:readme",
|
| 2938 |
"years": [
|
| 2939 |
2026,
|
| 2940 |
-
2025
|
|
|
|
| 2941 |
]
|
| 2942 |
},
|
| 2943 |
"bio.protein-interactions": {
|
| 2944 |
"query": "\"protein-protein interaction prediction\" in:readme",
|
| 2945 |
"years": [
|
| 2946 |
2026,
|
| 2947 |
-
2025
|
|
|
|
| 2948 |
]
|
| 2949 |
},
|
| 2950 |
"bio.protein-structure": {
|
| 2951 |
"query": "\"protein structure prediction\" in:description",
|
| 2952 |
"years": [
|
| 2953 |
2026,
|
| 2954 |
-
2025
|
|
|
|
| 2955 |
]
|
| 2956 |
},
|
| 2957 |
"bio.regulatory-sequence-modeling": {
|
| 2958 |
"query": "enhancer prediction genomics in:description,readme",
|
| 2959 |
"years": [
|
| 2960 |
2026,
|
| 2961 |
-
2025
|
|
|
|
| 2962 |
]
|
| 2963 |
},
|
| 2964 |
"bio.rna-language-models": {
|
| 2965 |
"query": "\"RNA language model\" in:description",
|
| 2966 |
"years": [
|
| 2967 |
2026,
|
| 2968 |
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2025
|
|
|
|
| 2969 |
]
|
| 2970 |
},
|
| 2971 |
"bio.rna-structure": {
|
|
@@ -3246,77 +3268,88 @@
|
|
| 3246 |
"query": "\"gradient-based optimization\" in:description",
|
| 3247 |
"years": [
|
| 3248 |
2026,
|
| 3249 |
-
2025
|
|
|
|
| 3250 |
]
|
| 3251 |
},
|
| 3252 |
"efficiency.hyperparameter-optimization": {
|
| 3253 |
"query": "\"hyperparameter optimization\" in:description",
|
| 3254 |
"years": [
|
| 3255 |
2026,
|
| 3256 |
-
2025
|
|
|
|
| 3257 |
]
|
| 3258 |
},
|
| 3259 |
"efficiency.inference-systems": {
|
| 3260 |
"query": "\"inference engine\" \"machine learning\" in:description,readme",
|
| 3261 |
"years": [
|
| 3262 |
2026,
|
| 3263 |
-
2025
|
|
|
|
| 3264 |
]
|
| 3265 |
},
|
| 3266 |
"efficiency.knowledge-distillation": {
|
| 3267 |
"query": "\"knowledge distillation\" in:description",
|
| 3268 |
"years": [
|
| 3269 |
2026,
|
| 3270 |
-
2025
|
|
|
|
| 3271 |
]
|
| 3272 |
},
|
| 3273 |
"efficiency.kv-cache": {
|
| 3274 |
"query": "\"KV cache\" in:description",
|
| 3275 |
"years": [
|
| 3276 |
2026,
|
| 3277 |
-
2025
|
|
|
|
| 3278 |
]
|
| 3279 |
},
|
| 3280 |
"efficiency.lora": {
|
| 3281 |
"query": "LoRA in:description",
|
| 3282 |
"years": [
|
| 3283 |
2026,
|
| 3284 |
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2025
|
|
|
|
| 3285 |
]
|
| 3286 |
},
|
| 3287 |
"efficiency.low-rank-factorization": {
|
| 3288 |
"query": "\"low-rank factorization\" in:description",
|
| 3289 |
"years": [
|
| 3290 |
2026,
|
| 3291 |
-
2025
|
|
|
|
| 3292 |
]
|
| 3293 |
},
|
| 3294 |
"efficiency.mixed-precision-training": {
|
| 3295 |
"query": "\"mixed precision training\" in:description",
|
| 3296 |
"years": [
|
| 3297 |
2026,
|
| 3298 |
-
2025
|
|
|
|
| 3299 |
]
|
| 3300 |
},
|
| 3301 |
"efficiency.mixture-of-experts": {
|
| 3302 |
"query": "\"mixture of experts\" in:description",
|
| 3303 |
"years": [
|
| 3304 |
2026,
|
| 3305 |
-
2025
|
|
|
|
| 3306 |
]
|
| 3307 |
},
|
| 3308 |
"efficiency.model-compression": {
|
| 3309 |
"query": "\"model compression\" in:description",
|
| 3310 |
"years": [
|
| 3311 |
2026,
|
| 3312 |
-
2025
|
|
|
|
| 3313 |
]
|
| 3314 |
},
|
| 3315 |
"efficiency.neural-architecture-search": {
|
| 3316 |
"query": "\"neural architecture search\" in:description",
|
| 3317 |
"years": [
|
| 3318 |
2026,
|
| 3319 |
-
2025
|
|
|
|
| 3320 |
]
|
| 3321 |
},
|
| 3322 |
"efficiency.optimizer-state-sharding": {
|
|
@@ -3451,77 +3484,88 @@
|
|
| 3451 |
"query": "\"heterogeneous treatment effects\" machine learning economics in:description,readme",
|
| 3452 |
"years": [
|
| 3453 |
2026,
|
| 3454 |
-
2025
|
|
|
|
| 3455 |
]
|
| 3456 |
},
|
| 3457 |
"gap2026.econometrics-policy-learning": {
|
| 3458 |
"query": "\"policy learning\" causal machine learning economics in:description,readme",
|
| 3459 |
"years": [
|
| 3460 |
2026,
|
| 3461 |
-
2025
|
|
|
|
| 3462 |
]
|
| 3463 |
},
|
| 3464 |
"gap2026.forecasting-count-data": {
|
| 3465 |
"query": "\"count time series forecasting\" neural in:description,readme",
|
| 3466 |
"years": [
|
| 3467 |
2026,
|
| 3468 |
-
2025
|
|
|
|
| 3469 |
]
|
| 3470 |
},
|
| 3471 |
"gap2026.forecasting-hierarchical": {
|
| 3472 |
"query": "\"hierarchical time series forecasting\" machine learning in:description,readme",
|
| 3473 |
"years": [
|
| 3474 |
2026,
|
| 3475 |
-
2025
|
|
|
|
| 3476 |
]
|
| 3477 |
},
|
| 3478 |
"gap2026.forecasting-intermittent-demand": {
|
| 3479 |
"query": "\"intermittent demand forecasting\" machine learning in:description,readme",
|
| 3480 |
"years": [
|
| 3481 |
2026,
|
| 3482 |
-
2025
|
|
|
|
| 3483 |
]
|
| 3484 |
},
|
| 3485 |
"gap2026.forecasting-quantile": {
|
| 3486 |
"query": "\"neural quantile forecasting\" in:description,readme",
|
| 3487 |
"years": [
|
| 3488 |
2026,
|
| 3489 |
-
2025
|
|
|
|
| 3490 |
]
|
| 3491 |
},
|
| 3492 |
"gap2026.green-ai-carbon": {
|
| 3493 |
"query": "\"carbon emissions\" machine learning training in:description,readme",
|
| 3494 |
"years": [
|
| 3495 |
2026,
|
| 3496 |
-
2025
|
|
|
|
| 3497 |
]
|
| 3498 |
},
|
| 3499 |
"gap2026.green-ai-carbon-aware-scheduling": {
|
| 3500 |
"query": "\"carbon-aware\" machine learning scheduling in:description,readme",
|
| 3501 |
"years": [
|
| 3502 |
2026,
|
| 3503 |
-
2025
|
|
|
|
| 3504 |
]
|
| 3505 |
},
|
| 3506 |
"gap2026.green-ai-efficient-inference": {
|
| 3507 |
"query": "\"energy efficient inference\" neural network in:description,readme",
|
| 3508 |
"years": [
|
| 3509 |
2026,
|
| 3510 |
-
2025
|
|
|
|
| 3511 |
]
|
| 3512 |
},
|
| 3513 |
"gap2026.green-ai-energy": {
|
| 3514 |
"query": "\"energy efficient machine learning\" in:description,readme",
|
| 3515 |
"years": [
|
| 3516 |
2026,
|
| 3517 |
-
2025
|
|
|
|
| 3518 |
]
|
| 3519 |
},
|
| 3520 |
"gap2026.math-learned-optimization": {
|
| 3521 |
"query": "\"learned optimizer\" optimization algorithm in:description,readme",
|
| 3522 |
"years": [
|
| 3523 |
2026,
|
| 3524 |
-
2025
|
|
|
|
| 3525 |
]
|
| 3526 |
},
|
| 3527 |
"gap2026.math-neural-combinatorial-optimization": {
|
|
@@ -3663,77 +3707,88 @@
|
|
| 3663 |
"query": "\"decision tree\" \"machine learning\" in:description,readme",
|
| 3664 |
"years": [
|
| 3665 |
2026,
|
| 3666 |
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2025
|
|
|
|
| 3667 |
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|
| 3668 |
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|
| 3669 |
"general.deep-learning-description": {
|
| 3670 |
"query": "\"deep learning\" in:description",
|
| 3671 |
"years": [
|
| 3672 |
2026,
|
| 3673 |
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2025
|
|
|
|
| 3674 |
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|
| 3675 |
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|
| 3676 |
"general.deep-learning-readme": {
|
| 3677 |
"query": "\"deep learning\" in:readme",
|
| 3678 |
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|
| 3679 |
2026,
|
| 3680 |
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2025
|
|
|
|
| 3681 |
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|
| 3682 |
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|
| 3683 |
"general.dimensionality-reduction": {
|
| 3684 |
"query": "\"dimensionality reduction\" in:description,readme",
|
| 3685 |
"years": [
|
| 3686 |
2026,
|
| 3687 |
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2025
|
|
|
|
| 3688 |
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|
| 3689 |
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|
| 3690 |
"general.domain-adaptation": {
|
| 3691 |
"query": "\"domain adaptation\" \"machine learning\" in:description,readme",
|
| 3692 |
"years": [
|
| 3693 |
2026,
|
| 3694 |
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2025
|
|
|
|
| 3695 |
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|
| 3696 |
},
|
| 3697 |
"general.gaussian-mixture-models": {
|
| 3698 |
"query": "\"Gaussian mixture model\" in:description,readme",
|
| 3699 |
"years": [
|
| 3700 |
2026,
|
| 3701 |
-
2025
|
|
|
|
| 3702 |
]
|
| 3703 |
},
|
| 3704 |
"general.gaussian-process": {
|
| 3705 |
"query": "\"Gaussian process\" in:description",
|
| 3706 |
"years": [
|
| 3707 |
2026,
|
| 3708 |
-
2025
|
|
|
|
| 3709 |
]
|
| 3710 |
},
|
| 3711 |
"general.gradient-boosting": {
|
| 3712 |
"query": "\"gradient boosting\" in:description",
|
| 3713 |
"years": [
|
| 3714 |
2026,
|
| 3715 |
-
2025
|
|
|
|
| 3716 |
]
|
| 3717 |
},
|
| 3718 |
"general.hidden-markov-models": {
|
| 3719 |
"query": "\"hidden Markov model\" \"machine learning\" in:description,readme",
|
| 3720 |
"years": [
|
| 3721 |
2026,
|
| 3722 |
-
2025
|
|
|
|
| 3723 |
]
|
| 3724 |
},
|
| 3725 |
"general.logistic-regression": {
|
| 3726 |
"query": "\"logistic regression\" in:description,readme",
|
| 3727 |
"years": [
|
| 3728 |
2026,
|
| 3729 |
-
2025
|
|
|
|
| 3730 |
]
|
| 3731 |
},
|
| 3732 |
"general.machine-learning-description": {
|
| 3733 |
"query": "\"machine learning\" in:description",
|
| 3734 |
"years": [
|
| 3735 |
2026,
|
| 3736 |
-
2025
|
|
|
|
| 3737 |
]
|
| 3738 |
},
|
| 3739 |
"general.machine-learning-readme": {
|
|
@@ -3980,77 +4035,88 @@
|
|
| 3980 |
"query": "\"geospatial knowledge graph\" in:description,readme",
|
| 3981 |
"years": [
|
| 3982 |
2026,
|
| 3983 |
-
2025
|
|
|
|
| 3984 |
]
|
| 3985 |
},
|
| 3986 |
"geo.hydrology": {
|
| 3987 |
"query": "\"hydrology machine learning\" in:readme",
|
| 3988 |
"years": [
|
| 3989 |
2026,
|
| 3990 |
-
2025
|
|
|
|
| 3991 |
]
|
| 3992 |
},
|
| 3993 |
"geo.land-cover": {
|
| 3994 |
"query": "\"land cover\" in:readme",
|
| 3995 |
"years": [
|
| 3996 |
2026,
|
| 3997 |
-
2025
|
|
|
|
| 3998 |
]
|
| 3999 |
},
|
| 4000 |
"geo.land-use": {
|
| 4001 |
"query": "\"land use\" in:readme",
|
| 4002 |
"years": [
|
| 4003 |
2026,
|
| 4004 |
-
2025
|
|
|
|
| 4005 |
]
|
| 4006 |
},
|
| 4007 |
"geo.lidar": {
|
| 4008 |
"query": "LiDAR in:description \"deep learning\"",
|
| 4009 |
"years": [
|
| 4010 |
2026,
|
| 4011 |
-
2025
|
|
|
|
| 4012 |
]
|
| 4013 |
},
|
| 4014 |
"geo.mobility-modeling": {
|
| 4015 |
"query": "\"human mobility\" \"machine learning\" in:description,readme",
|
| 4016 |
"years": [
|
| 4017 |
2026,
|
| 4018 |
-
2025
|
|
|
|
| 4019 |
]
|
| 4020 |
},
|
| 4021 |
"geo.object-detection": {
|
| 4022 |
"query": "\"object detection\" \"remote sensing\" in:description,readme",
|
| 4023 |
"years": [
|
| 4024 |
2026,
|
| 4025 |
-
2025
|
|
|
|
| 4026 |
]
|
| 4027 |
},
|
| 4028 |
"geo.ocean-remote-sensing": {
|
| 4029 |
"query": "\"ocean remote sensing\" in:description,readme",
|
| 4030 |
"years": [
|
| 4031 |
2026,
|
| 4032 |
-
2025
|
|
|
|
| 4033 |
]
|
| 4034 |
},
|
| 4035 |
"geo.precipitation-forecasting": {
|
| 4036 |
"query": "\"precipitation forecasting\" in:description,readme",
|
| 4037 |
"years": [
|
| 4038 |
2026,
|
| 4039 |
-
2025
|
|
|
|
| 4040 |
]
|
| 4041 |
},
|
| 4042 |
"geo.sar-imagery": {
|
| 4043 |
"query": "\"synthetic aperture radar\" in:readme",
|
| 4044 |
"years": [
|
| 4045 |
2026,
|
| 4046 |
-
2025
|
|
|
|
| 4047 |
]
|
| 4048 |
},
|
| 4049 |
"geo.satellite-imagery": {
|
| 4050 |
"query": "\"satellite imagery\" in:readme",
|
| 4051 |
"years": [
|
| 4052 |
2026,
|
| 4053 |
-
2025
|
|
|
|
| 4054 |
]
|
| 4055 |
},
|
| 4056 |
"geo.topic-earth-observation": {
|
|
@@ -4178,77 +4244,88 @@
|
|
| 4178 |
"query": "\"graph generation\" in:readme",
|
| 4179 |
"years": [
|
| 4180 |
2026,
|
| 4181 |
-
2025
|
|
|
|
| 4182 |
]
|
| 4183 |
},
|
| 4184 |
"graph.graph-transformer": {
|
| 4185 |
"query": "\"graph transformer\" in:description",
|
| 4186 |
"years": [
|
| 4187 |
2026,
|
| 4188 |
-
2025
|
|
|
|
| 4189 |
]
|
| 4190 |
},
|
| 4191 |
"graph.hypergraph-neural-network": {
|
| 4192 |
"query": "\"hypergraph neural network\" in:description",
|
| 4193 |
"years": [
|
| 4194 |
2026,
|
| 4195 |
-
2025
|
|
|
|
| 4196 |
]
|
| 4197 |
},
|
| 4198 |
"graph.knowledge-graph-embedding": {
|
| 4199 |
"query": "\"knowledge graph embedding\" in:description",
|
| 4200 |
"years": [
|
| 4201 |
2026,
|
| 4202 |
-
2025
|
|
|
|
| 4203 |
]
|
| 4204 |
},
|
| 4205 |
"graph.knowledge-graphs": {
|
| 4206 |
"query": "topic:knowledge-graph",
|
| 4207 |
"years": [
|
| 4208 |
2026,
|
| 4209 |
-
2025
|
|
|
|
| 4210 |
]
|
| 4211 |
},
|
| 4212 |
"graph.link-prediction": {
|
| 4213 |
"query": "\"link prediction\" in:description",
|
| 4214 |
"years": [
|
| 4215 |
2026,
|
| 4216 |
-
2025
|
|
|
|
| 4217 |
]
|
| 4218 |
},
|
| 4219 |
"graph.manifold-learning": {
|
| 4220 |
"query": "\"manifold learning\" in:description",
|
| 4221 |
"years": [
|
| 4222 |
2026,
|
| 4223 |
-
2025
|
|
|
|
| 4224 |
]
|
| 4225 |
},
|
| 4226 |
"graph.mesh-graph-learning": {
|
| 4227 |
"query": "\"mesh graph neural network\" in:description",
|
| 4228 |
"years": [
|
| 4229 |
2026,
|
| 4230 |
-
2025
|
|
|
|
| 4231 |
]
|
| 4232 |
},
|
| 4233 |
"graph.molecular-graphs": {
|
| 4234 |
"query": "\"molecular graph neural network\" in:readme",
|
| 4235 |
"years": [
|
| 4236 |
2026,
|
| 4237 |
-
2025
|
|
|
|
| 4238 |
]
|
| 4239 |
},
|
| 4240 |
"graph.neural-ode-graph": {
|
| 4241 |
"query": "\"graph neural ODE\" in:description",
|
| 4242 |
"years": [
|
| 4243 |
2026,
|
| 4244 |
-
2025
|
|
|
|
| 4245 |
]
|
| 4246 |
},
|
| 4247 |
"graph.persistent-homology": {
|
| 4248 |
"query": "\"persistent homology\" in:description",
|
| 4249 |
"years": [
|
| 4250 |
2026,
|
| 4251 |
-
2025
|
|
|
|
| 4252 |
]
|
| 4253 |
},
|
| 4254 |
"graph.point-cloud-learning": {
|
|
@@ -4408,77 +4485,88 @@
|
|
| 4408 |
"query": "\"instruction tuning\" in:readme",
|
| 4409 |
"years": [
|
| 4410 |
2026,
|
| 4411 |
-
2025
|
|
|
|
| 4412 |
]
|
| 4413 |
},
|
| 4414 |
"llm.language-model": {
|
| 4415 |
"query": "\"language model\" in:description",
|
| 4416 |
"years": [
|
| 4417 |
2026,
|
| 4418 |
-
2025
|
|
|
|
| 4419 |
]
|
| 4420 |
},
|
| 4421 |
"llm.language-models": {
|
| 4422 |
"query": "topic:large-language-models",
|
| 4423 |
"years": [
|
| 4424 |
2026,
|
| 4425 |
-
2025
|
|
|
|
| 4426 |
]
|
| 4427 |
},
|
| 4428 |
"llm.large-language-model": {
|
| 4429 |
"query": "\"large language model\" in:description",
|
| 4430 |
"years": [
|
| 4431 |
2026,
|
| 4432 |
-
2025
|
|
|
|
| 4433 |
]
|
| 4434 |
},
|
| 4435 |
"llm.long-context": {
|
| 4436 |
"query": "\"long context\" \"language model\" in:readme",
|
| 4437 |
"years": [
|
| 4438 |
2026,
|
| 4439 |
-
2025
|
|
|
|
| 4440 |
]
|
| 4441 |
},
|
| 4442 |
"llm.multimodal": {
|
| 4443 |
"query": "\"multimodal language model\" in:description",
|
| 4444 |
"years": [
|
| 4445 |
2026,
|
| 4446 |
-
2025
|
|
|
|
| 4447 |
]
|
| 4448 |
},
|
| 4449 |
"llm.parameter-efficient-finetuning": {
|
| 4450 |
"query": "\"parameter-efficient fine-tuning\" in:readme",
|
| 4451 |
"years": [
|
| 4452 |
2026,
|
| 4453 |
-
2025
|
|
|
|
| 4454 |
]
|
| 4455 |
},
|
| 4456 |
"llm.preference-optimization": {
|
| 4457 |
"query": "\"direct preference optimization\" in:readme",
|
| 4458 |
"years": [
|
| 4459 |
2026,
|
| 4460 |
-
2025
|
|
|
|
| 4461 |
]
|
| 4462 |
},
|
| 4463 |
"llm.quantization": {
|
| 4464 |
"query": "\"LLM quantization\" in:readme",
|
| 4465 |
"years": [
|
| 4466 |
2026,
|
| 4467 |
-
2025
|
|
|
|
| 4468 |
]
|
| 4469 |
},
|
| 4470 |
"llm.speculative-decoding": {
|
| 4471 |
"query": "\"speculative decoding\" in:readme",
|
| 4472 |
"years": [
|
| 4473 |
2026,
|
| 4474 |
-
2025
|
|
|
|
| 4475 |
]
|
| 4476 |
},
|
| 4477 |
"llm.synthetic-data": {
|
| 4478 |
"query": "\"synthetic data\" in:description",
|
| 4479 |
"years": [
|
| 4480 |
2026,
|
| 4481 |
-
2025
|
|
|
|
| 4482 |
]
|
| 4483 |
},
|
| 4484 |
"llm.synthetic-data-generation": {
|
|
@@ -4634,77 +4722,88 @@
|
|
| 4634 |
"query": "\"electronic health record\" in:readme",
|
| 4635 |
"years": [
|
| 4636 |
2026,
|
| 4637 |
-
2025
|
|
|
|
| 4638 |
]
|
| 4639 |
},
|
| 4640 |
"medical.genomics": {
|
| 4641 |
"query": "\"clinical genomics\" in:description,readme",
|
| 4642 |
"years": [
|
| 4643 |
2026,
|
| 4644 |
-
2025
|
|
|
|
| 4645 |
]
|
| 4646 |
},
|
| 4647 |
"medical.histopathology": {
|
| 4648 |
"query": "\"histopathology image analysis\" in:readme",
|
| 4649 |
"years": [
|
| 4650 |
2026,
|
| 4651 |
-
2025
|
|
|
|
| 4652 |
]
|
| 4653 |
},
|
| 4654 |
"medical.medical-image-reconstruction": {
|
| 4655 |
"query": "\"MRI reconstruction\" in:description,readme",
|
| 4656 |
"years": [
|
| 4657 |
2026,
|
| 4658 |
-
2025
|
|
|
|
| 4659 |
]
|
| 4660 |
},
|
| 4661 |
"medical.medical-image-registration": {
|
| 4662 |
"query": "\"medical image registration\" in:description,readme",
|
| 4663 |
"years": [
|
| 4664 |
2026,
|
| 4665 |
-
2025
|
|
|
|
| 4666 |
]
|
| 4667 |
},
|
| 4668 |
"medical.medical-image-segmentation": {
|
| 4669 |
"query": "\"medical image segmentation\" in:description",
|
| 4670 |
"years": [
|
| 4671 |
2026,
|
| 4672 |
-
2025
|
|
|
|
| 4673 |
]
|
| 4674 |
},
|
| 4675 |
"medical.medical-imaging": {
|
| 4676 |
"query": "\"medical imaging\" in:readme",
|
| 4677 |
"years": [
|
| 4678 |
2026,
|
| 4679 |
-
2025
|
|
|
|
| 4680 |
]
|
| 4681 |
},
|
| 4682 |
"medical.medical-language-model": {
|
| 4683 |
"query": "\"medical language model\" in:description",
|
| 4684 |
"years": [
|
| 4685 |
2026,
|
| 4686 |
-
2025
|
|
|
|
| 4687 |
]
|
| 4688 |
},
|
| 4689 |
"medical.medical-robotics": {
|
| 4690 |
"query": "\"surgical robotics\" \"machine learning\" in:description,readme",
|
| 4691 |
"years": [
|
| 4692 |
2026,
|
| 4693 |
-
2025
|
|
|
|
| 4694 |
]
|
| 4695 |
},
|
| 4696 |
"medical.neural-decoding": {
|
| 4697 |
"query": "\"neural data decoding\" in:description",
|
| 4698 |
"years": [
|
| 4699 |
2026,
|
| 4700 |
-
2025
|
|
|
|
| 4701 |
]
|
| 4702 |
},
|
| 4703 |
"medical.neuroimaging": {
|
| 4704 |
"query": "\"neuroimaging machine learning\" in:readme",
|
| 4705 |
"years": [
|
| 4706 |
2026,
|
| 4707 |
-
2025
|
|
|
|
| 4708 |
]
|
| 4709 |
},
|
| 4710 |
"medical.ophthalmology": {
|
|
@@ -4832,70 +4931,80 @@
|
|
| 4832 |
"query": "\"image to video\" in:readme",
|
| 4833 |
"years": [
|
| 4834 |
2026,
|
| 4835 |
-
2025
|
|
|
|
| 4836 |
]
|
| 4837 |
},
|
| 4838 |
"multimodal.motion-generation": {
|
| 4839 |
"query": "\"human motion generation\" in:readme",
|
| 4840 |
"years": [
|
| 4841 |
2026,
|
| 4842 |
-
2025
|
|
|
|
| 4843 |
]
|
| 4844 |
},
|
| 4845 |
"multimodal.nerf": {
|
| 4846 |
"query": "topic:nerf",
|
| 4847 |
"years": [
|
| 4848 |
2026,
|
| 4849 |
-
2025
|
|
|
|
| 4850 |
]
|
| 4851 |
},
|
| 4852 |
"multimodal.neural-rendering": {
|
| 4853 |
"query": "\"neural rendering\" \"radiance fields\" in:description",
|
| 4854 |
"years": [
|
| 4855 |
2026,
|
| 4856 |
-
2025
|
|
|
|
| 4857 |
]
|
| 4858 |
},
|
| 4859 |
"multimodal.point-cloud": {
|
| 4860 |
"query": "\"point cloud\" in:description",
|
| 4861 |
"years": [
|
| 4862 |
2026,
|
| 4863 |
-
2025
|
|
|
|
| 4864 |
]
|
| 4865 |
},
|
| 4866 |
"multimodal.scene-understanding": {
|
| 4867 |
"query": "\"scene understanding\" in:description",
|
| 4868 |
"years": [
|
| 4869 |
2026,
|
| 4870 |
-
2025
|
|
|
|
| 4871 |
]
|
| 4872 |
},
|
| 4873 |
"multimodal.text-to-3d": {
|
| 4874 |
"query": "\"text to 3D\" in:readme",
|
| 4875 |
"years": [
|
| 4876 |
2026,
|
| 4877 |
-
2025
|
|
|
|
| 4878 |
]
|
| 4879 |
},
|
| 4880 |
"multimodal.text-to-image": {
|
| 4881 |
"query": "\"text-to-image\" in:description",
|
| 4882 |
"years": [
|
| 4883 |
2026,
|
| 4884 |
-
2025
|
|
|
|
| 4885 |
]
|
| 4886 |
},
|
| 4887 |
"multimodal.text-to-video": {
|
| 4888 |
"query": "\"text-to-video\" in:description",
|
| 4889 |
"years": [
|
| 4890 |
2026,
|
| 4891 |
-
2025
|
|
|
|
| 4892 |
]
|
| 4893 |
},
|
| 4894 |
"multimodal.video-language-model": {
|
| 4895 |
"query": "\"video language model\" in:readme",
|
| 4896 |
"years": [
|
| 4897 |
2026,
|
| 4898 |
-
2025
|
|
|
|
| 4899 |
]
|
| 4900 |
},
|
| 4901 |
"multimodal.video-question-answering": {
|
|
@@ -5072,70 +5181,80 @@
|
|
| 5072 |
"query": "\"neural reranking\" in:description",
|
| 5073 |
"years": [
|
| 5074 |
2026,
|
| 5075 |
-
2025
|
|
|
|
| 5076 |
]
|
| 5077 |
},
|
| 5078 |
"nlp.question-answering": {
|
| 5079 |
"query": "\"question answering\" in:description",
|
| 5080 |
"years": [
|
| 5081 |
2026,
|
| 5082 |
-
2025
|
|
|
|
| 5083 |
]
|
| 5084 |
},
|
| 5085 |
"nlp.rag": {
|
| 5086 |
"query": "\"retrieval augmented generation\" in:description",
|
| 5087 |
"years": [
|
| 5088 |
2026,
|
| 5089 |
-
2025
|
|
|
|
| 5090 |
]
|
| 5091 |
},
|
| 5092 |
"nlp.semantic-search": {
|
| 5093 |
"query": "\"semantic search\" in:description",
|
| 5094 |
"years": [
|
| 5095 |
2026,
|
| 5096 |
-
2025
|
|
|
|
| 5097 |
]
|
| 5098 |
},
|
| 5099 |
"nlp.sentence-embeddings": {
|
| 5100 |
"query": "\"sentence embeddings\" in:description",
|
| 5101 |
"years": [
|
| 5102 |
2026,
|
| 5103 |
-
2025
|
|
|
|
| 5104 |
]
|
| 5105 |
},
|
| 5106 |
"nlp.subword-tokenization": {
|
| 5107 |
"query": "\"subword tokenization\" in:readme",
|
| 5108 |
"years": [
|
| 5109 |
2026,
|
| 5110 |
-
2025
|
|
|
|
| 5111 |
]
|
| 5112 |
},
|
| 5113 |
"nlp.text-classification": {
|
| 5114 |
"query": "\"text classification\" in:description",
|
| 5115 |
"years": [
|
| 5116 |
2026,
|
| 5117 |
-
2025
|
|
|
|
| 5118 |
]
|
| 5119 |
},
|
| 5120 |
"nlp.text-generation": {
|
| 5121 |
"query": "\"text generation\" in:readme",
|
| 5122 |
"years": [
|
| 5123 |
2026,
|
| 5124 |
-
2025
|
|
|
|
| 5125 |
]
|
| 5126 |
},
|
| 5127 |
"nlp.text-summarization": {
|
| 5128 |
"query": "\"text summarization\" in:description",
|
| 5129 |
"years": [
|
| 5130 |
2026,
|
| 5131 |
-
2025
|
|
|
|
| 5132 |
]
|
| 5133 |
},
|
| 5134 |
"nlp.topic-modeling": {
|
| 5135 |
"query": "\"topic modeling\" in:readme",
|
| 5136 |
"years": [
|
| 5137 |
2026,
|
| 5138 |
-
2025
|
|
|
|
| 5139 |
]
|
| 5140 |
},
|
| 5141 |
"recall.archaeological-remote-sensing": {
|
|
@@ -5214,70 +5333,80 @@
|
|
| 5214 |
"query": "\"grid stability prediction\" in:name,description,readme",
|
| 5215 |
"years": [
|
| 5216 |
2026,
|
| 5217 |
-
2025
|
|
|
|
| 5218 |
]
|
| 5219 |
},
|
| 5220 |
"recall.historical-document-recognition": {
|
| 5221 |
"query": "\"historical document recognition\" in:name,description,readme",
|
| 5222 |
"years": [
|
| 5223 |
2026,
|
| 5224 |
-
2025
|
|
|
|
| 5225 |
]
|
| 5226 |
},
|
| 5227 |
"recall.infrastructure-damage-detection": {
|
| 5228 |
"query": "\"infrastructure damage detection\" deep learning in:name,description,readme",
|
| 5229 |
"years": [
|
| 5230 |
2026,
|
| 5231 |
-
2025
|
|
|
|
| 5232 |
]
|
| 5233 |
},
|
| 5234 |
"recall.insurance-risk-modeling": {
|
| 5235 |
"query": "\"insurance risk\" machine learning in:name,description,readme",
|
| 5236 |
"years": [
|
| 5237 |
2026,
|
| 5238 |
-
2025
|
|
|
|
| 5239 |
]
|
| 5240 |
},
|
| 5241 |
"recall.legal-document-classification": {
|
| 5242 |
"query": "\"legal document classification\" in:name,description,readme",
|
| 5243 |
"years": [
|
| 5244 |
2026,
|
| 5245 |
-
2025
|
|
|
|
| 5246 |
]
|
| 5247 |
},
|
| 5248 |
"recall.legal-nlp": {
|
| 5249 |
"query": "legal NLP in:name,description,readme",
|
| 5250 |
"years": [
|
| 5251 |
2026,
|
| 5252 |
-
2025
|
|
|
|
| 5253 |
]
|
| 5254 |
},
|
| 5255 |
"recall.name.artificial-intelligence": {
|
| 5256 |
"query": "\"artificial intelligence\" in:name,description,readme",
|
| 5257 |
"years": [
|
| 5258 |
2026,
|
| 5259 |
-
2025
|
|
|
|
| 5260 |
]
|
| 5261 |
},
|
| 5262 |
"recall.name.deep-learning": {
|
| 5263 |
"query": "\"deep learning\" in:name,description,readme",
|
| 5264 |
"years": [
|
| 5265 |
2026,
|
| 5266 |
-
2025
|
|
|
|
| 5267 |
]
|
| 5268 |
},
|
| 5269 |
"recall.name.diffusion-model": {
|
| 5270 |
"query": "diffusion model in:name,description,readme",
|
| 5271 |
"years": [
|
| 5272 |
2026,
|
| 5273 |
-
2025
|
|
|
|
| 5274 |
]
|
| 5275 |
},
|
| 5276 |
"recall.name.foundation-model": {
|
| 5277 |
"query": "foundation model in:name,description,readme",
|
| 5278 |
"years": [
|
| 5279 |
2026,
|
| 5280 |
-
2025
|
|
|
|
| 5281 |
]
|
| 5282 |
},
|
| 5283 |
"recall.name.language-model": {
|
|
@@ -5511,70 +5640,80 @@
|
|
| 5511 |
"query": "\"imitation learning\" in:description",
|
| 5512 |
"years": [
|
| 5513 |
2026,
|
| 5514 |
-
2025
|
|
|
|
| 5515 |
]
|
| 5516 |
},
|
| 5517 |
"rl.inverse": {
|
| 5518 |
"query": "\"inverse reinforcement learning\" in:description",
|
| 5519 |
"years": [
|
| 5520 |
2026,
|
| 5521 |
-
2025
|
|
|
|
| 5522 |
]
|
| 5523 |
},
|
| 5524 |
"rl.model-based": {
|
| 5525 |
"query": "\"model-based reinforcement learning\" in:description",
|
| 5526 |
"years": [
|
| 5527 |
2026,
|
| 5528 |
-
2025
|
|
|
|
| 5529 |
]
|
| 5530 |
},
|
| 5531 |
"rl.model-free": {
|
| 5532 |
"query": "\"model-free reinforcement learning\" in:description",
|
| 5533 |
"years": [
|
| 5534 |
2026,
|
| 5535 |
-
2025
|
|
|
|
| 5536 |
]
|
| 5537 |
},
|
| 5538 |
"rl.multiagent": {
|
| 5539 |
"query": "\"multi-agent reinforcement learning\" in:description",
|
| 5540 |
"years": [
|
| 5541 |
2026,
|
| 5542 |
-
2025
|
|
|
|
| 5543 |
]
|
| 5544 |
},
|
| 5545 |
"rl.offline": {
|
| 5546 |
"query": "\"offline reinforcement learning\" in:description",
|
| 5547 |
"years": [
|
| 5548 |
2026,
|
| 5549 |
-
2025
|
|
|
|
| 5550 |
]
|
| 5551 |
},
|
| 5552 |
"rl.planning": {
|
| 5553 |
"query": "\"reinforcement learning planning\" in:description",
|
| 5554 |
"years": [
|
| 5555 |
2026,
|
| 5556 |
-
2025
|
|
|
|
| 5557 |
]
|
| 5558 |
},
|
| 5559 |
"rl.policy-gradient": {
|
| 5560 |
"query": "\"policy gradient\" in:description",
|
| 5561 |
"years": [
|
| 5562 |
2026,
|
| 5563 |
-
2025
|
|
|
|
| 5564 |
]
|
| 5565 |
},
|
| 5566 |
"rl.ppo": {
|
| 5567 |
"query": "\"proximal policy optimization\" in:description",
|
| 5568 |
"years": [
|
| 5569 |
2026,
|
| 5570 |
-
2025
|
|
|
|
| 5571 |
]
|
| 5572 |
},
|
| 5573 |
"rl.preference": {
|
| 5574 |
"query": "\"preference-based reinforcement learning\" in:description",
|
| 5575 |
"years": [
|
| 5576 |
2026,
|
| 5577 |
-
2025
|
|
|
|
| 5578 |
]
|
| 5579 |
},
|
| 5580 |
"rl.reinforcement-learning-from-human-feedback": {
|
|
@@ -5674,70 +5813,80 @@
|
|
| 5674 |
"query": "\"robot navigation\" in:description",
|
| 5675 |
"years": [
|
| 5676 |
2026,
|
| 5677 |
-
2025
|
|
|
|
| 5678 |
]
|
| 5679 |
},
|
| 5680 |
"robotics.robot-control": {
|
| 5681 |
"query": "\"robot control\" in:description",
|
| 5682 |
"years": [
|
| 5683 |
2026,
|
| 5684 |
-
2025
|
|
|
|
| 5685 |
]
|
| 5686 |
},
|
| 5687 |
"robotics.robot-foundation-model": {
|
| 5688 |
"query": "robot foundation model in:description,readme",
|
| 5689 |
"years": [
|
| 5690 |
2026,
|
| 5691 |
-
2025
|
|
|
|
| 5692 |
]
|
| 5693 |
},
|
| 5694 |
"robotics.robot-learning": {
|
| 5695 |
"query": "\"robot learning\" in:description",
|
| 5696 |
"years": [
|
| 5697 |
2026,
|
| 5698 |
-
2025
|
|
|
|
| 5699 |
]
|
| 5700 |
},
|
| 5701 |
"robotics.robot-manipulation-learning": {
|
| 5702 |
"query": "\"robot manipulation learning\" in:readme",
|
| 5703 |
"years": [
|
| 5704 |
2026,
|
| 5705 |
-
2025
|
|
|
|
| 5706 |
]
|
| 5707 |
},
|
| 5708 |
"robotics.robot-motion-planning": {
|
| 5709 |
"query": "\"robot motion planning\" in:description",
|
| 5710 |
"years": [
|
| 5711 |
2026,
|
| 5712 |
-
2025
|
|
|
|
| 5713 |
]
|
| 5714 |
},
|
| 5715 |
"robotics.robotics-reinforcement-learning": {
|
| 5716 |
"query": "\"robotics reinforcement learning\" in:description",
|
| 5717 |
"years": [
|
| 5718 |
2026,
|
| 5719 |
-
2025
|
|
|
|
| 5720 |
]
|
| 5721 |
},
|
| 5722 |
"robotics.robotics-topic": {
|
| 5723 |
"query": "topic:robotics",
|
| 5724 |
"years": [
|
| 5725 |
2026,
|
| 5726 |
-
2025
|
|
|
|
| 5727 |
]
|
| 5728 |
},
|
| 5729 |
"robotics.sim2real": {
|
| 5730 |
"query": "\"sim-to-real\" in:description",
|
| 5731 |
"years": [
|
| 5732 |
2026,
|
| 5733 |
-
2025
|
|
|
|
| 5734 |
]
|
| 5735 |
},
|
| 5736 |
"robotics.slam": {
|
| 5737 |
"query": "SLAM robotics in:description",
|
| 5738 |
"years": [
|
| 5739 |
2026,
|
| 5740 |
-
2025
|
|
|
|
| 5741 |
]
|
| 5742 |
},
|
| 5743 |
"robotics.tactile-learning": {
|
|
@@ -5836,77 +5985,88 @@
|
|
| 5836 |
"query": "fusion plasma in:description \"machine learning\"",
|
| 5837 |
"years": [
|
| 5838 |
2026,
|
| 5839 |
-
2025
|
|
|
|
| 5840 |
]
|
| 5841 |
},
|
| 5842 |
"science.gravitational-waves": {
|
| 5843 |
"query": "\"gravitational wave\" \"machine learning\" in:description,readme",
|
| 5844 |
"years": [
|
| 5845 |
2026,
|
| 5846 |
-
2025
|
|
|
|
| 5847 |
]
|
| 5848 |
},
|
| 5849 |
"science.inverse-problems": {
|
| 5850 |
"query": "\"inverse problems\" in:description",
|
| 5851 |
"years": [
|
| 5852 |
2026,
|
| 5853 |
-
2025
|
|
|
|
| 5854 |
]
|
| 5855 |
},
|
| 5856 |
"science.neural-operators": {
|
| 5857 |
"query": "\"neural operator\" in:description",
|
| 5858 |
"years": [
|
| 5859 |
2026,
|
| 5860 |
-
2025
|
|
|
|
| 5861 |
]
|
| 5862 |
},
|
| 5863 |
"science.ocean-modeling": {
|
| 5864 |
"query": "\"ocean modeling\" \"machine learning\" in:description,readme",
|
| 5865 |
"years": [
|
| 5866 |
2026,
|
| 5867 |
-
2025
|
|
|
|
| 5868 |
]
|
| 5869 |
},
|
| 5870 |
"science.particle-physics": {
|
| 5871 |
"query": "\"particle physics\" in:description",
|
| 5872 |
"years": [
|
| 5873 |
2026,
|
| 5874 |
-
2025
|
|
|
|
| 5875 |
]
|
| 5876 |
},
|
| 5877 |
"science.photonics": {
|
| 5878 |
"query": "photonics \"machine learning\" in:description,readme",
|
| 5879 |
"years": [
|
| 5880 |
2026,
|
| 5881 |
-
2025
|
|
|
|
| 5882 |
]
|
| 5883 |
},
|
| 5884 |
"science.physics": {
|
| 5885 |
"query": "physics in:description",
|
| 5886 |
"years": [
|
| 5887 |
2026,
|
| 5888 |
-
2025
|
|
|
|
| 5889 |
]
|
| 5890 |
},
|
| 5891 |
"science.physics-informed-neural-networks": {
|
| 5892 |
"query": "\"physics-informed neural network\" in:description",
|
| 5893 |
"years": [
|
| 5894 |
2026,
|
| 5895 |
-
2025
|
|
|
|
| 5896 |
]
|
| 5897 |
},
|
| 5898 |
"science.plasma-physics": {
|
| 5899 |
"query": "\"plasma physics\" in:description",
|
| 5900 |
"years": [
|
| 5901 |
2026,
|
| 5902 |
-
2025
|
|
|
|
| 5903 |
]
|
| 5904 |
},
|
| 5905 |
"science.quantum-materials": {
|
| 5906 |
"query": "\"quantum materials\" \"machine learning\" in:description,readme",
|
| 5907 |
"years": [
|
| 5908 |
2026,
|
| 5909 |
-
2025
|
|
|
|
| 5910 |
]
|
| 5911 |
},
|
| 5912 |
"science.quantum-physics": {
|
|
@@ -6026,49 +6186,56 @@
|
|
| 6026 |
"query": "\"fMRI decoding\" \"machine learning\" in:description,readme",
|
| 6027 |
"years": [
|
| 6028 |
2026,
|
| 6029 |
-
2025
|
|
|
|
| 6030 |
]
|
| 6031 |
},
|
| 6032 |
"specialized.machine-unlearning": {
|
| 6033 |
"query": "\"machine unlearning\" in:description,readme",
|
| 6034 |
"years": [
|
| 6035 |
2026,
|
| 6036 |
-
2025
|
|
|
|
| 6037 |
]
|
| 6038 |
},
|
| 6039 |
"specialized.mechanistic-interpretability": {
|
| 6040 |
"query": "\"mechanistic interpretability\" in:description,readme",
|
| 6041 |
"years": [
|
| 6042 |
2026,
|
| 6043 |
-
2025
|
|
|
|
| 6044 |
]
|
| 6045 |
},
|
| 6046 |
"specialized.medical-image-registration-deep-learning": {
|
| 6047 |
"query": "\"medical image registration\" \"deep learning\" in:description,readme",
|
| 6048 |
"years": [
|
| 6049 |
2026,
|
| 6050 |
-
2025
|
|
|
|
| 6051 |
]
|
| 6052 |
},
|
| 6053 |
"specialized.pathology-foundation-model": {
|
| 6054 |
"query": "\"pathology foundation model\" \"machine learning\" in:description,readme",
|
| 6055 |
"years": [
|
| 6056 |
2026,
|
| 6057 |
-
2025
|
|
|
|
| 6058 |
]
|
| 6059 |
},
|
| 6060 |
"specialized.spiking-neural-network": {
|
| 6061 |
"query": "\"spiking neural network\" in:description,readme",
|
| 6062 |
"years": [
|
| 6063 |
2026,
|
| 6064 |
-
2025
|
|
|
|
| 6065 |
]
|
| 6066 |
},
|
| 6067 |
"specialized.test-time-adaptation": {
|
| 6068 |
"query": "\"test-time adaptation\" in:description,readme",
|
| 6069 |
"years": [
|
| 6070 |
2026,
|
| 6071 |
-
2025
|
|
|
|
| 6072 |
]
|
| 6073 |
},
|
| 6074 |
"timeseries.anomaly-detection": {
|
|
@@ -6139,77 +6306,88 @@
|
|
| 6139 |
"query": "\"long horizon forecasting\" in:readme",
|
| 6140 |
"years": [
|
| 6141 |
2026,
|
| 6142 |
-
2025
|
|
|
|
| 6143 |
]
|
| 6144 |
},
|
| 6145 |
"timeseries.multivariate": {
|
| 6146 |
"query": "\"multivariate time series\" in:description",
|
| 6147 |
"years": [
|
| 6148 |
2026,
|
| 6149 |
-
2025
|
|
|
|
| 6150 |
]
|
| 6151 |
},
|
| 6152 |
"timeseries.nbeats": {
|
| 6153 |
"query": "N-BEATS in:description",
|
| 6154 |
"years": [
|
| 6155 |
2026,
|
| 6156 |
-
2025
|
|
|
|
| 6157 |
]
|
| 6158 |
},
|
| 6159 |
"timeseries.patchtst": {
|
| 6160 |
"query": "PatchTST in:description",
|
| 6161 |
"years": [
|
| 6162 |
2026,
|
| 6163 |
-
2025
|
|
|
|
| 6164 |
]
|
| 6165 |
},
|
| 6166 |
"timeseries.predictive-maintenance": {
|
| 6167 |
"query": "\"predictive maintenance\" in:description",
|
| 6168 |
"years": [
|
| 6169 |
2026,
|
| 6170 |
-
2025
|
|
|
|
| 6171 |
]
|
| 6172 |
},
|
| 6173 |
"timeseries.probabilistic-forecasting": {
|
| 6174 |
"query": "\"probabilistic forecasting\" in:readme",
|
| 6175 |
"years": [
|
| 6176 |
2026,
|
| 6177 |
-
2025
|
|
|
|
| 6178 |
]
|
| 6179 |
},
|
| 6180 |
"timeseries.remaining-useful-life": {
|
| 6181 |
"query": "\"remaining useful life\" in:readme",
|
| 6182 |
"years": [
|
| 6183 |
2026,
|
| 6184 |
-
2025
|
|
|
|
| 6185 |
]
|
| 6186 |
},
|
| 6187 |
"timeseries.sensor-data": {
|
| 6188 |
"query": "\"sensor time series\" in:description",
|
| 6189 |
"years": [
|
| 6190 |
2026,
|
| 6191 |
-
2025
|
|
|
|
| 6192 |
]
|
| 6193 |
},
|
| 6194 |
"timeseries.state-space-models": {
|
| 6195 |
"query": "\"state space model\" in:description",
|
| 6196 |
"years": [
|
| 6197 |
2026,
|
| 6198 |
-
2025
|
|
|
|
| 6199 |
]
|
| 6200 |
},
|
| 6201 |
"timeseries.streaming": {
|
| 6202 |
"query": "\"streaming time series\" in:readme",
|
| 6203 |
"years": [
|
| 6204 |
2026,
|
| 6205 |
-
2025
|
|
|
|
| 6206 |
]
|
| 6207 |
},
|
| 6208 |
"timeseries.synthetic-generation": {
|
| 6209 |
"query": "\"time series generation\" in:description,readme",
|
| 6210 |
"years": [
|
| 6211 |
2026,
|
| 6212 |
-
2025
|
|
|
|
| 6213 |
]
|
| 6214 |
},
|
| 6215 |
"timeseries.tabular-foundation-models": {
|
|
@@ -6329,77 +6507,88 @@
|
|
| 6329 |
"query": "\"causal machine learning\" in:description",
|
| 6330 |
"years": [
|
| 6331 |
2026,
|
| 6332 |
-
2025
|
|
|
|
| 6333 |
]
|
| 6334 |
},
|
| 6335 |
"trust.causal-representation-learning": {
|
| 6336 |
"query": "\"causal representation learning\" in:description",
|
| 6337 |
"years": [
|
| 6338 |
2026,
|
| 6339 |
-
2025
|
|
|
|
| 6340 |
]
|
| 6341 |
},
|
| 6342 |
"trust.conformal-prediction": {
|
| 6343 |
"query": "\"conformal prediction\" in:description",
|
| 6344 |
"years": [
|
| 6345 |
2026,
|
| 6346 |
-
2025
|
|
|
|
| 6347 |
]
|
| 6348 |
},
|
| 6349 |
"trust.counterfactual-explanations": {
|
| 6350 |
"query": "\"counterfactual explanation\" in:description",
|
| 6351 |
"years": [
|
| 6352 |
2026,
|
| 6353 |
-
2025
|
|
|
|
| 6354 |
]
|
| 6355 |
},
|
| 6356 |
"trust.differential-privacy": {
|
| 6357 |
"query": "\"differential privacy\" in:description",
|
| 6358 |
"years": [
|
| 6359 |
2026,
|
| 6360 |
-
2025
|
|
|
|
| 6361 |
]
|
| 6362 |
},
|
| 6363 |
"trust.distribution-shift": {
|
| 6364 |
"query": "\"distribution shift\" in:description",
|
| 6365 |
"years": [
|
| 6366 |
2026,
|
| 6367 |
-
2025
|
|
|
|
| 6368 |
]
|
| 6369 |
},
|
| 6370 |
"trust.domain-generalization": {
|
| 6371 |
"query": "\"domain generalization\" in:description",
|
| 6372 |
"years": [
|
| 6373 |
2026,
|
| 6374 |
-
2025
|
|
|
|
| 6375 |
]
|
| 6376 |
},
|
| 6377 |
"trust.explainable-ai": {
|
| 6378 |
"query": "\"explainable AI\" in:description",
|
| 6379 |
"years": [
|
| 6380 |
2026,
|
| 6381 |
-
2025
|
|
|
|
| 6382 |
]
|
| 6383 |
},
|
| 6384 |
"trust.federated-learning": {
|
| 6385 |
"query": "\"federated learning\" in:description",
|
| 6386 |
"years": [
|
| 6387 |
2026,
|
| 6388 |
-
2025
|
|
|
|
| 6389 |
]
|
| 6390 |
},
|
| 6391 |
"trust.instrumental-variable-ml": {
|
| 6392 |
"query": "\"double machine learning\" in:description",
|
| 6393 |
"years": [
|
| 6394 |
2026,
|
| 6395 |
-
2025
|
|
|
|
| 6396 |
]
|
| 6397 |
},
|
| 6398 |
"trust.interpretable-ml": {
|
| 6399 |
"query": "\"interpretable machine learning\" in:description",
|
| 6400 |
"years": [
|
| 6401 |
2026,
|
| 6402 |
-
2025
|
|
|
|
| 6403 |
]
|
| 6404 |
},
|
| 6405 |
"trust.membership-inference": {
|
|
@@ -6540,77 +6729,88 @@
|
|
| 6540 |
"query": "\"image retrieval\" in:readme",
|
| 6541 |
"years": [
|
| 6542 |
2026,
|
| 6543 |
-
2025
|
|
|
|
| 6544 |
]
|
| 6545 |
},
|
| 6546 |
"vision.image-super-resolution": {
|
| 6547 |
"query": "\"image super-resolution\" in:readme",
|
| 6548 |
"years": [
|
| 6549 |
2026,
|
| 6550 |
-
2025
|
|
|
|
| 6551 |
]
|
| 6552 |
},
|
| 6553 |
"vision.image-to-image-translation": {
|
| 6554 |
"query": "\"image-to-image translation\" in:readme",
|
| 6555 |
"years": [
|
| 6556 |
2026,
|
| 6557 |
-
2025
|
|
|
|
| 6558 |
]
|
| 6559 |
},
|
| 6560 |
"vision.neural-rendering": {
|
| 6561 |
"query": "\"neural rendering\" in:description",
|
| 6562 |
"years": [
|
| 6563 |
2026,
|
| 6564 |
-
2025
|
|
|
|
| 6565 |
]
|
| 6566 |
},
|
| 6567 |
"vision.object-detection": {
|
| 6568 |
"query": "\"object detection\" in:description",
|
| 6569 |
"years": [
|
| 6570 |
2026,
|
| 6571 |
-
2025
|
|
|
|
| 6572 |
]
|
| 6573 |
},
|
| 6574 |
"vision.object-tracking": {
|
| 6575 |
"query": "\"object tracking\" in:readme",
|
| 6576 |
"years": [
|
| 6577 |
2026,
|
| 6578 |
-
2025
|
|
|
|
| 6579 |
]
|
| 6580 |
},
|
| 6581 |
"vision.ocr": {
|
| 6582 |
"query": "topic:ocr",
|
| 6583 |
"years": [
|
| 6584 |
2026,
|
| 6585 |
-
2025
|
|
|
|
| 6586 |
]
|
| 6587 |
},
|
| 6588 |
"vision.open-vocabulary-detection": {
|
| 6589 |
"query": "\"open-vocabulary detection\" in:readme",
|
| 6590 |
"years": [
|
| 6591 |
2026,
|
| 6592 |
-
2025
|
|
|
|
| 6593 |
]
|
| 6594 |
},
|
| 6595 |
"vision.optical-flow": {
|
| 6596 |
"query": "topic:optical-flow",
|
| 6597 |
"years": [
|
| 6598 |
2026,
|
| 6599 |
-
2025
|
|
|
|
| 6600 |
]
|
| 6601 |
},
|
| 6602 |
"vision.pose-estimation": {
|
| 6603 |
"query": "\"human pose estimation\" in:readme",
|
| 6604 |
"years": [
|
| 6605 |
2026,
|
| 6606 |
-
2025
|
|
|
|
| 6607 |
]
|
| 6608 |
},
|
| 6609 |
"vision.promptable-segmentation": {
|
| 6610 |
"query": "\"promptable segmentation\" in:readme",
|
| 6611 |
"years": [
|
| 6612 |
2026,
|
| 6613 |
-
2025
|
|
|
|
| 6614 |
]
|
| 6615 |
},
|
| 6616 |
"vision.segmentation": {
|
|
@@ -6679,5 +6879,5 @@
|
|
| 6679 |
"end": "2026-09-24",
|
| 6680 |
"search_policy_version": 2,
|
| 6681 |
"start_year": 2008,
|
| 6682 |
-
"updated_at": "2026-
|
| 6683 |
}
|
|
|
|
| 2418 |
"query": "\"customer segmentation\" \"machine learning\" in:description,readme",
|
| 2419 |
"years": [
|
| 2420 |
2026,
|
| 2421 |
+
2025,
|
| 2422 |
+
2024
|
| 2423 |
]
|
| 2424 |
},
|
| 2425 |
"applied.cybersecurity-ml": {
|
| 2426 |
"query": "\"machine learning\" cybersecurity in:description,readme",
|
| 2427 |
"years": [
|
| 2428 |
2026,
|
| 2429 |
+
2025,
|
| 2430 |
+
2024
|
| 2431 |
]
|
| 2432 |
},
|
| 2433 |
"applied.demand-forecasting": {
|
| 2434 |
"query": "\"demand forecasting\" in:description",
|
| 2435 |
"years": [
|
| 2436 |
2026,
|
| 2437 |
+
2025,
|
| 2438 |
+
2024
|
| 2439 |
]
|
| 2440 |
},
|
| 2441 |
"applied.dynamic-pricing": {
|
| 2442 |
"query": "\"dynamic pricing\" \"machine learning\" in:description,readme",
|
| 2443 |
"years": [
|
| 2444 |
2026,
|
| 2445 |
+
2025,
|
| 2446 |
+
2024
|
| 2447 |
]
|
| 2448 |
},
|
| 2449 |
"applied.ecological-forecasting": {
|
| 2450 |
"query": "\"ecological forecasting\" \"machine learning\" in:description,readme",
|
| 2451 |
"years": [
|
| 2452 |
2026,
|
| 2453 |
+
2025,
|
| 2454 |
+
2024
|
| 2455 |
]
|
| 2456 |
},
|
| 2457 |
"applied.educational-data-mining": {
|
| 2458 |
"query": "\"educational data mining\" in:description,readme",
|
| 2459 |
"years": [
|
| 2460 |
2026,
|
| 2461 |
+
2025,
|
| 2462 |
+
2024
|
| 2463 |
]
|
| 2464 |
},
|
| 2465 |
"applied.energy-load-forecasting": {
|
| 2466 |
"query": "\"load forecasting\" energy in:description,readme",
|
| 2467 |
"years": [
|
| 2468 |
2026,
|
| 2469 |
+
2025,
|
| 2470 |
+
2024
|
| 2471 |
]
|
| 2472 |
},
|
| 2473 |
"applied.fraud-detection": {
|
| 2474 |
"query": "\"fraud detection\" \"machine learning\" in:description,readme",
|
| 2475 |
"years": [
|
| 2476 |
2026,
|
| 2477 |
+
2025,
|
| 2478 |
+
2024
|
| 2479 |
]
|
| 2480 |
},
|
| 2481 |
"applied.industrial-defect-detection": {
|
| 2482 |
"query": "\"industrial defect detection\" \"deep learning\" in:description,readme",
|
| 2483 |
"years": [
|
| 2484 |
2026,
|
| 2485 |
+
2025,
|
| 2486 |
+
2024
|
| 2487 |
]
|
| 2488 |
},
|
| 2489 |
"applied.intrusion-detection": {
|
| 2490 |
"query": "\"intrusion detection\" \"machine learning\" in:description,readme",
|
| 2491 |
"years": [
|
| 2492 |
2026,
|
| 2493 |
+
2025,
|
| 2494 |
+
2024
|
| 2495 |
]
|
| 2496 |
},
|
| 2497 |
"applied.inventory-optimization": {
|
| 2498 |
"query": "\"inventory optimization\" in:readme",
|
| 2499 |
"years": [
|
| 2500 |
2026,
|
| 2501 |
+
2025,
|
| 2502 |
+
2024
|
| 2503 |
]
|
| 2504 |
},
|
| 2505 |
"applied.learning-to-rank": {
|
|
|
|
| 2906 |
"query": "\"microbiome\" \"machine learning\" in:description,readme",
|
| 2907 |
"years": [
|
| 2908 |
2026,
|
| 2909 |
+
2025,
|
| 2910 |
+
2024
|
| 2911 |
]
|
| 2912 |
},
|
| 2913 |
"bio.microscopy-cell-analysis": {
|
| 2914 |
"query": "\"cell segmentation\" microscopy in:description,readme",
|
| 2915 |
"years": [
|
| 2916 |
2026,
|
| 2917 |
+
2025,
|
| 2918 |
+
2024
|
| 2919 |
]
|
| 2920 |
},
|
| 2921 |
"bio.molecular-dynamics": {
|
| 2922 |
"query": "\"molecular dynamics\" in:description",
|
| 2923 |
"years": [
|
| 2924 |
2026,
|
| 2925 |
+
2025,
|
| 2926 |
+
2024
|
| 2927 |
]
|
| 2928 |
},
|
| 2929 |
"bio.molecular-force-fields": {
|
| 2930 |
"query": "\"machine learning force field\" in:readme",
|
| 2931 |
"years": [
|
| 2932 |
2026,
|
| 2933 |
+
2025,
|
| 2934 |
+
2024
|
| 2935 |
]
|
| 2936 |
},
|
| 2937 |
"bio.phylogenetics": {
|
| 2938 |
"query": "\"phylogenetics\" in:description",
|
| 2939 |
"years": [
|
| 2940 |
2026,
|
| 2941 |
+
2025,
|
| 2942 |
+
2024
|
| 2943 |
]
|
| 2944 |
},
|
| 2945 |
"bio.protein-design": {
|
| 2946 |
"query": "\"protein design\" in:description",
|
| 2947 |
"years": [
|
| 2948 |
2026,
|
| 2949 |
+
2025,
|
| 2950 |
+
2024
|
| 2951 |
]
|
| 2952 |
},
|
| 2953 |
"bio.protein-folding": {
|
| 2954 |
"query": "\"protein folding\" in:readme",
|
| 2955 |
"years": [
|
| 2956 |
2026,
|
| 2957 |
+
2025,
|
| 2958 |
+
2024
|
| 2959 |
]
|
| 2960 |
},
|
| 2961 |
"bio.protein-interactions": {
|
| 2962 |
"query": "\"protein-protein interaction prediction\" in:readme",
|
| 2963 |
"years": [
|
| 2964 |
2026,
|
| 2965 |
+
2025,
|
| 2966 |
+
2024
|
| 2967 |
]
|
| 2968 |
},
|
| 2969 |
"bio.protein-structure": {
|
| 2970 |
"query": "\"protein structure prediction\" in:description",
|
| 2971 |
"years": [
|
| 2972 |
2026,
|
| 2973 |
+
2025,
|
| 2974 |
+
2024
|
| 2975 |
]
|
| 2976 |
},
|
| 2977 |
"bio.regulatory-sequence-modeling": {
|
| 2978 |
"query": "enhancer prediction genomics in:description,readme",
|
| 2979 |
"years": [
|
| 2980 |
2026,
|
| 2981 |
+
2025,
|
| 2982 |
+
2024
|
| 2983 |
]
|
| 2984 |
},
|
| 2985 |
"bio.rna-language-models": {
|
| 2986 |
"query": "\"RNA language model\" in:description",
|
| 2987 |
"years": [
|
| 2988 |
2026,
|
| 2989 |
+
2025,
|
| 2990 |
+
2024
|
| 2991 |
]
|
| 2992 |
},
|
| 2993 |
"bio.rna-structure": {
|
|
|
|
| 3268 |
"query": "\"gradient-based optimization\" in:description",
|
| 3269 |
"years": [
|
| 3270 |
2026,
|
| 3271 |
+
2025,
|
| 3272 |
+
2024
|
| 3273 |
]
|
| 3274 |
},
|
| 3275 |
"efficiency.hyperparameter-optimization": {
|
| 3276 |
"query": "\"hyperparameter optimization\" in:description",
|
| 3277 |
"years": [
|
| 3278 |
2026,
|
| 3279 |
+
2025,
|
| 3280 |
+
2024
|
| 3281 |
]
|
| 3282 |
},
|
| 3283 |
"efficiency.inference-systems": {
|
| 3284 |
"query": "\"inference engine\" \"machine learning\" in:description,readme",
|
| 3285 |
"years": [
|
| 3286 |
2026,
|
| 3287 |
+
2025,
|
| 3288 |
+
2024
|
| 3289 |
]
|
| 3290 |
},
|
| 3291 |
"efficiency.knowledge-distillation": {
|
| 3292 |
"query": "\"knowledge distillation\" in:description",
|
| 3293 |
"years": [
|
| 3294 |
2026,
|
| 3295 |
+
2025,
|
| 3296 |
+
2024
|
| 3297 |
]
|
| 3298 |
},
|
| 3299 |
"efficiency.kv-cache": {
|
| 3300 |
"query": "\"KV cache\" in:description",
|
| 3301 |
"years": [
|
| 3302 |
2026,
|
| 3303 |
+
2025,
|
| 3304 |
+
2024
|
| 3305 |
]
|
| 3306 |
},
|
| 3307 |
"efficiency.lora": {
|
| 3308 |
"query": "LoRA in:description",
|
| 3309 |
"years": [
|
| 3310 |
2026,
|
| 3311 |
+
2025,
|
| 3312 |
+
2024
|
| 3313 |
]
|
| 3314 |
},
|
| 3315 |
"efficiency.low-rank-factorization": {
|
| 3316 |
"query": "\"low-rank factorization\" in:description",
|
| 3317 |
"years": [
|
| 3318 |
2026,
|
| 3319 |
+
2025,
|
| 3320 |
+
2024
|
| 3321 |
]
|
| 3322 |
},
|
| 3323 |
"efficiency.mixed-precision-training": {
|
| 3324 |
"query": "\"mixed precision training\" in:description",
|
| 3325 |
"years": [
|
| 3326 |
2026,
|
| 3327 |
+
2025,
|
| 3328 |
+
2024
|
| 3329 |
]
|
| 3330 |
},
|
| 3331 |
"efficiency.mixture-of-experts": {
|
| 3332 |
"query": "\"mixture of experts\" in:description",
|
| 3333 |
"years": [
|
| 3334 |
2026,
|
| 3335 |
+
2025,
|
| 3336 |
+
2024
|
| 3337 |
]
|
| 3338 |
},
|
| 3339 |
"efficiency.model-compression": {
|
| 3340 |
"query": "\"model compression\" in:description",
|
| 3341 |
"years": [
|
| 3342 |
2026,
|
| 3343 |
+
2025,
|
| 3344 |
+
2024
|
| 3345 |
]
|
| 3346 |
},
|
| 3347 |
"efficiency.neural-architecture-search": {
|
| 3348 |
"query": "\"neural architecture search\" in:description",
|
| 3349 |
"years": [
|
| 3350 |
2026,
|
| 3351 |
+
2025,
|
| 3352 |
+
2024
|
| 3353 |
]
|
| 3354 |
},
|
| 3355 |
"efficiency.optimizer-state-sharding": {
|
|
|
|
| 3484 |
"query": "\"heterogeneous treatment effects\" machine learning economics in:description,readme",
|
| 3485 |
"years": [
|
| 3486 |
2026,
|
| 3487 |
+
2025,
|
| 3488 |
+
2024
|
| 3489 |
]
|
| 3490 |
},
|
| 3491 |
"gap2026.econometrics-policy-learning": {
|
| 3492 |
"query": "\"policy learning\" causal machine learning economics in:description,readme",
|
| 3493 |
"years": [
|
| 3494 |
2026,
|
| 3495 |
+
2025,
|
| 3496 |
+
2024
|
| 3497 |
]
|
| 3498 |
},
|
| 3499 |
"gap2026.forecasting-count-data": {
|
| 3500 |
"query": "\"count time series forecasting\" neural in:description,readme",
|
| 3501 |
"years": [
|
| 3502 |
2026,
|
| 3503 |
+
2025,
|
| 3504 |
+
2024
|
| 3505 |
]
|
| 3506 |
},
|
| 3507 |
"gap2026.forecasting-hierarchical": {
|
| 3508 |
"query": "\"hierarchical time series forecasting\" machine learning in:description,readme",
|
| 3509 |
"years": [
|
| 3510 |
2026,
|
| 3511 |
+
2025,
|
| 3512 |
+
2024
|
| 3513 |
]
|
| 3514 |
},
|
| 3515 |
"gap2026.forecasting-intermittent-demand": {
|
| 3516 |
"query": "\"intermittent demand forecasting\" machine learning in:description,readme",
|
| 3517 |
"years": [
|
| 3518 |
2026,
|
| 3519 |
+
2025,
|
| 3520 |
+
2024
|
| 3521 |
]
|
| 3522 |
},
|
| 3523 |
"gap2026.forecasting-quantile": {
|
| 3524 |
"query": "\"neural quantile forecasting\" in:description,readme",
|
| 3525 |
"years": [
|
| 3526 |
2026,
|
| 3527 |
+
2025,
|
| 3528 |
+
2024
|
| 3529 |
]
|
| 3530 |
},
|
| 3531 |
"gap2026.green-ai-carbon": {
|
| 3532 |
"query": "\"carbon emissions\" machine learning training in:description,readme",
|
| 3533 |
"years": [
|
| 3534 |
2026,
|
| 3535 |
+
2025,
|
| 3536 |
+
2024
|
| 3537 |
]
|
| 3538 |
},
|
| 3539 |
"gap2026.green-ai-carbon-aware-scheduling": {
|
| 3540 |
"query": "\"carbon-aware\" machine learning scheduling in:description,readme",
|
| 3541 |
"years": [
|
| 3542 |
2026,
|
| 3543 |
+
2025,
|
| 3544 |
+
2024
|
| 3545 |
]
|
| 3546 |
},
|
| 3547 |
"gap2026.green-ai-efficient-inference": {
|
| 3548 |
"query": "\"energy efficient inference\" neural network in:description,readme",
|
| 3549 |
"years": [
|
| 3550 |
2026,
|
| 3551 |
+
2025,
|
| 3552 |
+
2024
|
| 3553 |
]
|
| 3554 |
},
|
| 3555 |
"gap2026.green-ai-energy": {
|
| 3556 |
"query": "\"energy efficient machine learning\" in:description,readme",
|
| 3557 |
"years": [
|
| 3558 |
2026,
|
| 3559 |
+
2025,
|
| 3560 |
+
2024
|
| 3561 |
]
|
| 3562 |
},
|
| 3563 |
"gap2026.math-learned-optimization": {
|
| 3564 |
"query": "\"learned optimizer\" optimization algorithm in:description,readme",
|
| 3565 |
"years": [
|
| 3566 |
2026,
|
| 3567 |
+
2025,
|
| 3568 |
+
2024
|
| 3569 |
]
|
| 3570 |
},
|
| 3571 |
"gap2026.math-neural-combinatorial-optimization": {
|
|
|
|
| 3707 |
"query": "\"decision tree\" \"machine learning\" in:description,readme",
|
| 3708 |
"years": [
|
| 3709 |
2026,
|
| 3710 |
+
2025,
|
| 3711 |
+
2024
|
| 3712 |
]
|
| 3713 |
},
|
| 3714 |
"general.deep-learning-description": {
|
| 3715 |
"query": "\"deep learning\" in:description",
|
| 3716 |
"years": [
|
| 3717 |
2026,
|
| 3718 |
+
2025,
|
| 3719 |
+
2024
|
| 3720 |
]
|
| 3721 |
},
|
| 3722 |
"general.deep-learning-readme": {
|
| 3723 |
"query": "\"deep learning\" in:readme",
|
| 3724 |
"years": [
|
| 3725 |
2026,
|
| 3726 |
+
2025,
|
| 3727 |
+
2024
|
| 3728 |
]
|
| 3729 |
},
|
| 3730 |
"general.dimensionality-reduction": {
|
| 3731 |
"query": "\"dimensionality reduction\" in:description,readme",
|
| 3732 |
"years": [
|
| 3733 |
2026,
|
| 3734 |
+
2025,
|
| 3735 |
+
2024
|
| 3736 |
]
|
| 3737 |
},
|
| 3738 |
"general.domain-adaptation": {
|
| 3739 |
"query": "\"domain adaptation\" \"machine learning\" in:description,readme",
|
| 3740 |
"years": [
|
| 3741 |
2026,
|
| 3742 |
+
2025,
|
| 3743 |
+
2024
|
| 3744 |
]
|
| 3745 |
},
|
| 3746 |
"general.gaussian-mixture-models": {
|
| 3747 |
"query": "\"Gaussian mixture model\" in:description,readme",
|
| 3748 |
"years": [
|
| 3749 |
2026,
|
| 3750 |
+
2025,
|
| 3751 |
+
2024
|
| 3752 |
]
|
| 3753 |
},
|
| 3754 |
"general.gaussian-process": {
|
| 3755 |
"query": "\"Gaussian process\" in:description",
|
| 3756 |
"years": [
|
| 3757 |
2026,
|
| 3758 |
+
2025,
|
| 3759 |
+
2024
|
| 3760 |
]
|
| 3761 |
},
|
| 3762 |
"general.gradient-boosting": {
|
| 3763 |
"query": "\"gradient boosting\" in:description",
|
| 3764 |
"years": [
|
| 3765 |
2026,
|
| 3766 |
+
2025,
|
| 3767 |
+
2024
|
| 3768 |
]
|
| 3769 |
},
|
| 3770 |
"general.hidden-markov-models": {
|
| 3771 |
"query": "\"hidden Markov model\" \"machine learning\" in:description,readme",
|
| 3772 |
"years": [
|
| 3773 |
2026,
|
| 3774 |
+
2025,
|
| 3775 |
+
2024
|
| 3776 |
]
|
| 3777 |
},
|
| 3778 |
"general.logistic-regression": {
|
| 3779 |
"query": "\"logistic regression\" in:description,readme",
|
| 3780 |
"years": [
|
| 3781 |
2026,
|
| 3782 |
+
2025,
|
| 3783 |
+
2024
|
| 3784 |
]
|
| 3785 |
},
|
| 3786 |
"general.machine-learning-description": {
|
| 3787 |
"query": "\"machine learning\" in:description",
|
| 3788 |
"years": [
|
| 3789 |
2026,
|
| 3790 |
+
2025,
|
| 3791 |
+
2024
|
| 3792 |
]
|
| 3793 |
},
|
| 3794 |
"general.machine-learning-readme": {
|
|
|
|
| 4035 |
"query": "\"geospatial knowledge graph\" in:description,readme",
|
| 4036 |
"years": [
|
| 4037 |
2026,
|
| 4038 |
+
2025,
|
| 4039 |
+
2024
|
| 4040 |
]
|
| 4041 |
},
|
| 4042 |
"geo.hydrology": {
|
| 4043 |
"query": "\"hydrology machine learning\" in:readme",
|
| 4044 |
"years": [
|
| 4045 |
2026,
|
| 4046 |
+
2025,
|
| 4047 |
+
2024
|
| 4048 |
]
|
| 4049 |
},
|
| 4050 |
"geo.land-cover": {
|
| 4051 |
"query": "\"land cover\" in:readme",
|
| 4052 |
"years": [
|
| 4053 |
2026,
|
| 4054 |
+
2025,
|
| 4055 |
+
2024
|
| 4056 |
]
|
| 4057 |
},
|
| 4058 |
"geo.land-use": {
|
| 4059 |
"query": "\"land use\" in:readme",
|
| 4060 |
"years": [
|
| 4061 |
2026,
|
| 4062 |
+
2025,
|
| 4063 |
+
2024
|
| 4064 |
]
|
| 4065 |
},
|
| 4066 |
"geo.lidar": {
|
| 4067 |
"query": "LiDAR in:description \"deep learning\"",
|
| 4068 |
"years": [
|
| 4069 |
2026,
|
| 4070 |
+
2025,
|
| 4071 |
+
2024
|
| 4072 |
]
|
| 4073 |
},
|
| 4074 |
"geo.mobility-modeling": {
|
| 4075 |
"query": "\"human mobility\" \"machine learning\" in:description,readme",
|
| 4076 |
"years": [
|
| 4077 |
2026,
|
| 4078 |
+
2025,
|
| 4079 |
+
2024
|
| 4080 |
]
|
| 4081 |
},
|
| 4082 |
"geo.object-detection": {
|
| 4083 |
"query": "\"object detection\" \"remote sensing\" in:description,readme",
|
| 4084 |
"years": [
|
| 4085 |
2026,
|
| 4086 |
+
2025,
|
| 4087 |
+
2024
|
| 4088 |
]
|
| 4089 |
},
|
| 4090 |
"geo.ocean-remote-sensing": {
|
| 4091 |
"query": "\"ocean remote sensing\" in:description,readme",
|
| 4092 |
"years": [
|
| 4093 |
2026,
|
| 4094 |
+
2025,
|
| 4095 |
+
2024
|
| 4096 |
]
|
| 4097 |
},
|
| 4098 |
"geo.precipitation-forecasting": {
|
| 4099 |
"query": "\"precipitation forecasting\" in:description,readme",
|
| 4100 |
"years": [
|
| 4101 |
2026,
|
| 4102 |
+
2025,
|
| 4103 |
+
2024
|
| 4104 |
]
|
| 4105 |
},
|
| 4106 |
"geo.sar-imagery": {
|
| 4107 |
"query": "\"synthetic aperture radar\" in:readme",
|
| 4108 |
"years": [
|
| 4109 |
2026,
|
| 4110 |
+
2025,
|
| 4111 |
+
2024
|
| 4112 |
]
|
| 4113 |
},
|
| 4114 |
"geo.satellite-imagery": {
|
| 4115 |
"query": "\"satellite imagery\" in:readme",
|
| 4116 |
"years": [
|
| 4117 |
2026,
|
| 4118 |
+
2025,
|
| 4119 |
+
2024
|
| 4120 |
]
|
| 4121 |
},
|
| 4122 |
"geo.topic-earth-observation": {
|
|
|
|
| 4244 |
"query": "\"graph generation\" in:readme",
|
| 4245 |
"years": [
|
| 4246 |
2026,
|
| 4247 |
+
2025,
|
| 4248 |
+
2024
|
| 4249 |
]
|
| 4250 |
},
|
| 4251 |
"graph.graph-transformer": {
|
| 4252 |
"query": "\"graph transformer\" in:description",
|
| 4253 |
"years": [
|
| 4254 |
2026,
|
| 4255 |
+
2025,
|
| 4256 |
+
2024
|
| 4257 |
]
|
| 4258 |
},
|
| 4259 |
"graph.hypergraph-neural-network": {
|
| 4260 |
"query": "\"hypergraph neural network\" in:description",
|
| 4261 |
"years": [
|
| 4262 |
2026,
|
| 4263 |
+
2025,
|
| 4264 |
+
2024
|
| 4265 |
]
|
| 4266 |
},
|
| 4267 |
"graph.knowledge-graph-embedding": {
|
| 4268 |
"query": "\"knowledge graph embedding\" in:description",
|
| 4269 |
"years": [
|
| 4270 |
2026,
|
| 4271 |
+
2025,
|
| 4272 |
+
2024
|
| 4273 |
]
|
| 4274 |
},
|
| 4275 |
"graph.knowledge-graphs": {
|
| 4276 |
"query": "topic:knowledge-graph",
|
| 4277 |
"years": [
|
| 4278 |
2026,
|
| 4279 |
+
2025,
|
| 4280 |
+
2024
|
| 4281 |
]
|
| 4282 |
},
|
| 4283 |
"graph.link-prediction": {
|
| 4284 |
"query": "\"link prediction\" in:description",
|
| 4285 |
"years": [
|
| 4286 |
2026,
|
| 4287 |
+
2025,
|
| 4288 |
+
2024
|
| 4289 |
]
|
| 4290 |
},
|
| 4291 |
"graph.manifold-learning": {
|
| 4292 |
"query": "\"manifold learning\" in:description",
|
| 4293 |
"years": [
|
| 4294 |
2026,
|
| 4295 |
+
2025,
|
| 4296 |
+
2024
|
| 4297 |
]
|
| 4298 |
},
|
| 4299 |
"graph.mesh-graph-learning": {
|
| 4300 |
"query": "\"mesh graph neural network\" in:description",
|
| 4301 |
"years": [
|
| 4302 |
2026,
|
| 4303 |
+
2025,
|
| 4304 |
+
2024
|
| 4305 |
]
|
| 4306 |
},
|
| 4307 |
"graph.molecular-graphs": {
|
| 4308 |
"query": "\"molecular graph neural network\" in:readme",
|
| 4309 |
"years": [
|
| 4310 |
2026,
|
| 4311 |
+
2025,
|
| 4312 |
+
2024
|
| 4313 |
]
|
| 4314 |
},
|
| 4315 |
"graph.neural-ode-graph": {
|
| 4316 |
"query": "\"graph neural ODE\" in:description",
|
| 4317 |
"years": [
|
| 4318 |
2026,
|
| 4319 |
+
2025,
|
| 4320 |
+
2024
|
| 4321 |
]
|
| 4322 |
},
|
| 4323 |
"graph.persistent-homology": {
|
| 4324 |
"query": "\"persistent homology\" in:description",
|
| 4325 |
"years": [
|
| 4326 |
2026,
|
| 4327 |
+
2025,
|
| 4328 |
+
2024
|
| 4329 |
]
|
| 4330 |
},
|
| 4331 |
"graph.point-cloud-learning": {
|
|
|
|
| 4485 |
"query": "\"instruction tuning\" in:readme",
|
| 4486 |
"years": [
|
| 4487 |
2026,
|
| 4488 |
+
2025,
|
| 4489 |
+
2024
|
| 4490 |
]
|
| 4491 |
},
|
| 4492 |
"llm.language-model": {
|
| 4493 |
"query": "\"language model\" in:description",
|
| 4494 |
"years": [
|
| 4495 |
2026,
|
| 4496 |
+
2025,
|
| 4497 |
+
2024
|
| 4498 |
]
|
| 4499 |
},
|
| 4500 |
"llm.language-models": {
|
| 4501 |
"query": "topic:large-language-models",
|
| 4502 |
"years": [
|
| 4503 |
2026,
|
| 4504 |
+
2025,
|
| 4505 |
+
2024
|
| 4506 |
]
|
| 4507 |
},
|
| 4508 |
"llm.large-language-model": {
|
| 4509 |
"query": "\"large language model\" in:description",
|
| 4510 |
"years": [
|
| 4511 |
2026,
|
| 4512 |
+
2025,
|
| 4513 |
+
2024
|
| 4514 |
]
|
| 4515 |
},
|
| 4516 |
"llm.long-context": {
|
| 4517 |
"query": "\"long context\" \"language model\" in:readme",
|
| 4518 |
"years": [
|
| 4519 |
2026,
|
| 4520 |
+
2025,
|
| 4521 |
+
2024
|
| 4522 |
]
|
| 4523 |
},
|
| 4524 |
"llm.multimodal": {
|
| 4525 |
"query": "\"multimodal language model\" in:description",
|
| 4526 |
"years": [
|
| 4527 |
2026,
|
| 4528 |
+
2025,
|
| 4529 |
+
2024
|
| 4530 |
]
|
| 4531 |
},
|
| 4532 |
"llm.parameter-efficient-finetuning": {
|
| 4533 |
"query": "\"parameter-efficient fine-tuning\" in:readme",
|
| 4534 |
"years": [
|
| 4535 |
2026,
|
| 4536 |
+
2025,
|
| 4537 |
+
2024
|
| 4538 |
]
|
| 4539 |
},
|
| 4540 |
"llm.preference-optimization": {
|
| 4541 |
"query": "\"direct preference optimization\" in:readme",
|
| 4542 |
"years": [
|
| 4543 |
2026,
|
| 4544 |
+
2025,
|
| 4545 |
+
2024
|
| 4546 |
]
|
| 4547 |
},
|
| 4548 |
"llm.quantization": {
|
| 4549 |
"query": "\"LLM quantization\" in:readme",
|
| 4550 |
"years": [
|
| 4551 |
2026,
|
| 4552 |
+
2025,
|
| 4553 |
+
2024
|
| 4554 |
]
|
| 4555 |
},
|
| 4556 |
"llm.speculative-decoding": {
|
| 4557 |
"query": "\"speculative decoding\" in:readme",
|
| 4558 |
"years": [
|
| 4559 |
2026,
|
| 4560 |
+
2025,
|
| 4561 |
+
2024
|
| 4562 |
]
|
| 4563 |
},
|
| 4564 |
"llm.synthetic-data": {
|
| 4565 |
"query": "\"synthetic data\" in:description",
|
| 4566 |
"years": [
|
| 4567 |
2026,
|
| 4568 |
+
2025,
|
| 4569 |
+
2024
|
| 4570 |
]
|
| 4571 |
},
|
| 4572 |
"llm.synthetic-data-generation": {
|
|
|
|
| 4722 |
"query": "\"electronic health record\" in:readme",
|
| 4723 |
"years": [
|
| 4724 |
2026,
|
| 4725 |
+
2025,
|
| 4726 |
+
2024
|
| 4727 |
]
|
| 4728 |
},
|
| 4729 |
"medical.genomics": {
|
| 4730 |
"query": "\"clinical genomics\" in:description,readme",
|
| 4731 |
"years": [
|
| 4732 |
2026,
|
| 4733 |
+
2025,
|
| 4734 |
+
2024
|
| 4735 |
]
|
| 4736 |
},
|
| 4737 |
"medical.histopathology": {
|
| 4738 |
"query": "\"histopathology image analysis\" in:readme",
|
| 4739 |
"years": [
|
| 4740 |
2026,
|
| 4741 |
+
2025,
|
| 4742 |
+
2024
|
| 4743 |
]
|
| 4744 |
},
|
| 4745 |
"medical.medical-image-reconstruction": {
|
| 4746 |
"query": "\"MRI reconstruction\" in:description,readme",
|
| 4747 |
"years": [
|
| 4748 |
2026,
|
| 4749 |
+
2025,
|
| 4750 |
+
2024
|
| 4751 |
]
|
| 4752 |
},
|
| 4753 |
"medical.medical-image-registration": {
|
| 4754 |
"query": "\"medical image registration\" in:description,readme",
|
| 4755 |
"years": [
|
| 4756 |
2026,
|
| 4757 |
+
2025,
|
| 4758 |
+
2024
|
| 4759 |
]
|
| 4760 |
},
|
| 4761 |
"medical.medical-image-segmentation": {
|
| 4762 |
"query": "\"medical image segmentation\" in:description",
|
| 4763 |
"years": [
|
| 4764 |
2026,
|
| 4765 |
+
2025,
|
| 4766 |
+
2024
|
| 4767 |
]
|
| 4768 |
},
|
| 4769 |
"medical.medical-imaging": {
|
| 4770 |
"query": "\"medical imaging\" in:readme",
|
| 4771 |
"years": [
|
| 4772 |
2026,
|
| 4773 |
+
2025,
|
| 4774 |
+
2024
|
| 4775 |
]
|
| 4776 |
},
|
| 4777 |
"medical.medical-language-model": {
|
| 4778 |
"query": "\"medical language model\" in:description",
|
| 4779 |
"years": [
|
| 4780 |
2026,
|
| 4781 |
+
2025,
|
| 4782 |
+
2024
|
| 4783 |
]
|
| 4784 |
},
|
| 4785 |
"medical.medical-robotics": {
|
| 4786 |
"query": "\"surgical robotics\" \"machine learning\" in:description,readme",
|
| 4787 |
"years": [
|
| 4788 |
2026,
|
| 4789 |
+
2025,
|
| 4790 |
+
2024
|
| 4791 |
]
|
| 4792 |
},
|
| 4793 |
"medical.neural-decoding": {
|
| 4794 |
"query": "\"neural data decoding\" in:description",
|
| 4795 |
"years": [
|
| 4796 |
2026,
|
| 4797 |
+
2025,
|
| 4798 |
+
2024
|
| 4799 |
]
|
| 4800 |
},
|
| 4801 |
"medical.neuroimaging": {
|
| 4802 |
"query": "\"neuroimaging machine learning\" in:readme",
|
| 4803 |
"years": [
|
| 4804 |
2026,
|
| 4805 |
+
2025,
|
| 4806 |
+
2024
|
| 4807 |
]
|
| 4808 |
},
|
| 4809 |
"medical.ophthalmology": {
|
|
|
|
| 4931 |
"query": "\"image to video\" in:readme",
|
| 4932 |
"years": [
|
| 4933 |
2026,
|
| 4934 |
+
2025,
|
| 4935 |
+
2024
|
| 4936 |
]
|
| 4937 |
},
|
| 4938 |
"multimodal.motion-generation": {
|
| 4939 |
"query": "\"human motion generation\" in:readme",
|
| 4940 |
"years": [
|
| 4941 |
2026,
|
| 4942 |
+
2025,
|
| 4943 |
+
2024
|
| 4944 |
]
|
| 4945 |
},
|
| 4946 |
"multimodal.nerf": {
|
| 4947 |
"query": "topic:nerf",
|
| 4948 |
"years": [
|
| 4949 |
2026,
|
| 4950 |
+
2025,
|
| 4951 |
+
2024
|
| 4952 |
]
|
| 4953 |
},
|
| 4954 |
"multimodal.neural-rendering": {
|
| 4955 |
"query": "\"neural rendering\" \"radiance fields\" in:description",
|
| 4956 |
"years": [
|
| 4957 |
2026,
|
| 4958 |
+
2025,
|
| 4959 |
+
2024
|
| 4960 |
]
|
| 4961 |
},
|
| 4962 |
"multimodal.point-cloud": {
|
| 4963 |
"query": "\"point cloud\" in:description",
|
| 4964 |
"years": [
|
| 4965 |
2026,
|
| 4966 |
+
2025,
|
| 4967 |
+
2024
|
| 4968 |
]
|
| 4969 |
},
|
| 4970 |
"multimodal.scene-understanding": {
|
| 4971 |
"query": "\"scene understanding\" in:description",
|
| 4972 |
"years": [
|
| 4973 |
2026,
|
| 4974 |
+
2025,
|
| 4975 |
+
2024
|
| 4976 |
]
|
| 4977 |
},
|
| 4978 |
"multimodal.text-to-3d": {
|
| 4979 |
"query": "\"text to 3D\" in:readme",
|
| 4980 |
"years": [
|
| 4981 |
2026,
|
| 4982 |
+
2025,
|
| 4983 |
+
2024
|
| 4984 |
]
|
| 4985 |
},
|
| 4986 |
"multimodal.text-to-image": {
|
| 4987 |
"query": "\"text-to-image\" in:description",
|
| 4988 |
"years": [
|
| 4989 |
2026,
|
| 4990 |
+
2025,
|
| 4991 |
+
2024
|
| 4992 |
]
|
| 4993 |
},
|
| 4994 |
"multimodal.text-to-video": {
|
| 4995 |
"query": "\"text-to-video\" in:description",
|
| 4996 |
"years": [
|
| 4997 |
2026,
|
| 4998 |
+
2025,
|
| 4999 |
+
2024
|
| 5000 |
]
|
| 5001 |
},
|
| 5002 |
"multimodal.video-language-model": {
|
| 5003 |
"query": "\"video language model\" in:readme",
|
| 5004 |
"years": [
|
| 5005 |
2026,
|
| 5006 |
+
2025,
|
| 5007 |
+
2024
|
| 5008 |
]
|
| 5009 |
},
|
| 5010 |
"multimodal.video-question-answering": {
|
|
|
|
| 5181 |
"query": "\"neural reranking\" in:description",
|
| 5182 |
"years": [
|
| 5183 |
2026,
|
| 5184 |
+
2025,
|
| 5185 |
+
2024
|
| 5186 |
]
|
| 5187 |
},
|
| 5188 |
"nlp.question-answering": {
|
| 5189 |
"query": "\"question answering\" in:description",
|
| 5190 |
"years": [
|
| 5191 |
2026,
|
| 5192 |
+
2025,
|
| 5193 |
+
2024
|
| 5194 |
]
|
| 5195 |
},
|
| 5196 |
"nlp.rag": {
|
| 5197 |
"query": "\"retrieval augmented generation\" in:description",
|
| 5198 |
"years": [
|
| 5199 |
2026,
|
| 5200 |
+
2025,
|
| 5201 |
+
2024
|
| 5202 |
]
|
| 5203 |
},
|
| 5204 |
"nlp.semantic-search": {
|
| 5205 |
"query": "\"semantic search\" in:description",
|
| 5206 |
"years": [
|
| 5207 |
2026,
|
| 5208 |
+
2025,
|
| 5209 |
+
2024
|
| 5210 |
]
|
| 5211 |
},
|
| 5212 |
"nlp.sentence-embeddings": {
|
| 5213 |
"query": "\"sentence embeddings\" in:description",
|
| 5214 |
"years": [
|
| 5215 |
2026,
|
| 5216 |
+
2025,
|
| 5217 |
+
2024
|
| 5218 |
]
|
| 5219 |
},
|
| 5220 |
"nlp.subword-tokenization": {
|
| 5221 |
"query": "\"subword tokenization\" in:readme",
|
| 5222 |
"years": [
|
| 5223 |
2026,
|
| 5224 |
+
2025,
|
| 5225 |
+
2024
|
| 5226 |
]
|
| 5227 |
},
|
| 5228 |
"nlp.text-classification": {
|
| 5229 |
"query": "\"text classification\" in:description",
|
| 5230 |
"years": [
|
| 5231 |
2026,
|
| 5232 |
+
2025,
|
| 5233 |
+
2024
|
| 5234 |
]
|
| 5235 |
},
|
| 5236 |
"nlp.text-generation": {
|
| 5237 |
"query": "\"text generation\" in:readme",
|
| 5238 |
"years": [
|
| 5239 |
2026,
|
| 5240 |
+
2025,
|
| 5241 |
+
2024
|
| 5242 |
]
|
| 5243 |
},
|
| 5244 |
"nlp.text-summarization": {
|
| 5245 |
"query": "\"text summarization\" in:description",
|
| 5246 |
"years": [
|
| 5247 |
2026,
|
| 5248 |
+
2025,
|
| 5249 |
+
2024
|
| 5250 |
]
|
| 5251 |
},
|
| 5252 |
"nlp.topic-modeling": {
|
| 5253 |
"query": "\"topic modeling\" in:readme",
|
| 5254 |
"years": [
|
| 5255 |
2026,
|
| 5256 |
+
2025,
|
| 5257 |
+
2024
|
| 5258 |
]
|
| 5259 |
},
|
| 5260 |
"recall.archaeological-remote-sensing": {
|
|
|
|
| 5333 |
"query": "\"grid stability prediction\" in:name,description,readme",
|
| 5334 |
"years": [
|
| 5335 |
2026,
|
| 5336 |
+
2025,
|
| 5337 |
+
2024
|
| 5338 |
]
|
| 5339 |
},
|
| 5340 |
"recall.historical-document-recognition": {
|
| 5341 |
"query": "\"historical document recognition\" in:name,description,readme",
|
| 5342 |
"years": [
|
| 5343 |
2026,
|
| 5344 |
+
2025,
|
| 5345 |
+
2024
|
| 5346 |
]
|
| 5347 |
},
|
| 5348 |
"recall.infrastructure-damage-detection": {
|
| 5349 |
"query": "\"infrastructure damage detection\" deep learning in:name,description,readme",
|
| 5350 |
"years": [
|
| 5351 |
2026,
|
| 5352 |
+
2025,
|
| 5353 |
+
2024
|
| 5354 |
]
|
| 5355 |
},
|
| 5356 |
"recall.insurance-risk-modeling": {
|
| 5357 |
"query": "\"insurance risk\" machine learning in:name,description,readme",
|
| 5358 |
"years": [
|
| 5359 |
2026,
|
| 5360 |
+
2025,
|
| 5361 |
+
2024
|
| 5362 |
]
|
| 5363 |
},
|
| 5364 |
"recall.legal-document-classification": {
|
| 5365 |
"query": "\"legal document classification\" in:name,description,readme",
|
| 5366 |
"years": [
|
| 5367 |
2026,
|
| 5368 |
+
2025,
|
| 5369 |
+
2024
|
| 5370 |
]
|
| 5371 |
},
|
| 5372 |
"recall.legal-nlp": {
|
| 5373 |
"query": "legal NLP in:name,description,readme",
|
| 5374 |
"years": [
|
| 5375 |
2026,
|
| 5376 |
+
2025,
|
| 5377 |
+
2024
|
| 5378 |
]
|
| 5379 |
},
|
| 5380 |
"recall.name.artificial-intelligence": {
|
| 5381 |
"query": "\"artificial intelligence\" in:name,description,readme",
|
| 5382 |
"years": [
|
| 5383 |
2026,
|
| 5384 |
+
2025,
|
| 5385 |
+
2024
|
| 5386 |
]
|
| 5387 |
},
|
| 5388 |
"recall.name.deep-learning": {
|
| 5389 |
"query": "\"deep learning\" in:name,description,readme",
|
| 5390 |
"years": [
|
| 5391 |
2026,
|
| 5392 |
+
2025,
|
| 5393 |
+
2024
|
| 5394 |
]
|
| 5395 |
},
|
| 5396 |
"recall.name.diffusion-model": {
|
| 5397 |
"query": "diffusion model in:name,description,readme",
|
| 5398 |
"years": [
|
| 5399 |
2026,
|
| 5400 |
+
2025,
|
| 5401 |
+
2024
|
| 5402 |
]
|
| 5403 |
},
|
| 5404 |
"recall.name.foundation-model": {
|
| 5405 |
"query": "foundation model in:name,description,readme",
|
| 5406 |
"years": [
|
| 5407 |
2026,
|
| 5408 |
+
2025,
|
| 5409 |
+
2024
|
| 5410 |
]
|
| 5411 |
},
|
| 5412 |
"recall.name.language-model": {
|
|
|
|
| 5640 |
"query": "\"imitation learning\" in:description",
|
| 5641 |
"years": [
|
| 5642 |
2026,
|
| 5643 |
+
2025,
|
| 5644 |
+
2024
|
| 5645 |
]
|
| 5646 |
},
|
| 5647 |
"rl.inverse": {
|
| 5648 |
"query": "\"inverse reinforcement learning\" in:description",
|
| 5649 |
"years": [
|
| 5650 |
2026,
|
| 5651 |
+
2025,
|
| 5652 |
+
2024
|
| 5653 |
]
|
| 5654 |
},
|
| 5655 |
"rl.model-based": {
|
| 5656 |
"query": "\"model-based reinforcement learning\" in:description",
|
| 5657 |
"years": [
|
| 5658 |
2026,
|
| 5659 |
+
2025,
|
| 5660 |
+
2024
|
| 5661 |
]
|
| 5662 |
},
|
| 5663 |
"rl.model-free": {
|
| 5664 |
"query": "\"model-free reinforcement learning\" in:description",
|
| 5665 |
"years": [
|
| 5666 |
2026,
|
| 5667 |
+
2025,
|
| 5668 |
+
2024
|
| 5669 |
]
|
| 5670 |
},
|
| 5671 |
"rl.multiagent": {
|
| 5672 |
"query": "\"multi-agent reinforcement learning\" in:description",
|
| 5673 |
"years": [
|
| 5674 |
2026,
|
| 5675 |
+
2025,
|
| 5676 |
+
2024
|
| 5677 |
]
|
| 5678 |
},
|
| 5679 |
"rl.offline": {
|
| 5680 |
"query": "\"offline reinforcement learning\" in:description",
|
| 5681 |
"years": [
|
| 5682 |
2026,
|
| 5683 |
+
2025,
|
| 5684 |
+
2024
|
| 5685 |
]
|
| 5686 |
},
|
| 5687 |
"rl.planning": {
|
| 5688 |
"query": "\"reinforcement learning planning\" in:description",
|
| 5689 |
"years": [
|
| 5690 |
2026,
|
| 5691 |
+
2025,
|
| 5692 |
+
2024
|
| 5693 |
]
|
| 5694 |
},
|
| 5695 |
"rl.policy-gradient": {
|
| 5696 |
"query": "\"policy gradient\" in:description",
|
| 5697 |
"years": [
|
| 5698 |
2026,
|
| 5699 |
+
2025,
|
| 5700 |
+
2024
|
| 5701 |
]
|
| 5702 |
},
|
| 5703 |
"rl.ppo": {
|
| 5704 |
"query": "\"proximal policy optimization\" in:description",
|
| 5705 |
"years": [
|
| 5706 |
2026,
|
| 5707 |
+
2025,
|
| 5708 |
+
2024
|
| 5709 |
]
|
| 5710 |
},
|
| 5711 |
"rl.preference": {
|
| 5712 |
"query": "\"preference-based reinforcement learning\" in:description",
|
| 5713 |
"years": [
|
| 5714 |
2026,
|
| 5715 |
+
2025,
|
| 5716 |
+
2024
|
| 5717 |
]
|
| 5718 |
},
|
| 5719 |
"rl.reinforcement-learning-from-human-feedback": {
|
|
|
|
| 5813 |
"query": "\"robot navigation\" in:description",
|
| 5814 |
"years": [
|
| 5815 |
2026,
|
| 5816 |
+
2025,
|
| 5817 |
+
2024
|
| 5818 |
]
|
| 5819 |
},
|
| 5820 |
"robotics.robot-control": {
|
| 5821 |
"query": "\"robot control\" in:description",
|
| 5822 |
"years": [
|
| 5823 |
2026,
|
| 5824 |
+
2025,
|
| 5825 |
+
2024
|
| 5826 |
]
|
| 5827 |
},
|
| 5828 |
"robotics.robot-foundation-model": {
|
| 5829 |
"query": "robot foundation model in:description,readme",
|
| 5830 |
"years": [
|
| 5831 |
2026,
|
| 5832 |
+
2025,
|
| 5833 |
+
2024
|
| 5834 |
]
|
| 5835 |
},
|
| 5836 |
"robotics.robot-learning": {
|
| 5837 |
"query": "\"robot learning\" in:description",
|
| 5838 |
"years": [
|
| 5839 |
2026,
|
| 5840 |
+
2025,
|
| 5841 |
+
2024
|
| 5842 |
]
|
| 5843 |
},
|
| 5844 |
"robotics.robot-manipulation-learning": {
|
| 5845 |
"query": "\"robot manipulation learning\" in:readme",
|
| 5846 |
"years": [
|
| 5847 |
2026,
|
| 5848 |
+
2025,
|
| 5849 |
+
2024
|
| 5850 |
]
|
| 5851 |
},
|
| 5852 |
"robotics.robot-motion-planning": {
|
| 5853 |
"query": "\"robot motion planning\" in:description",
|
| 5854 |
"years": [
|
| 5855 |
2026,
|
| 5856 |
+
2025,
|
| 5857 |
+
2024
|
| 5858 |
]
|
| 5859 |
},
|
| 5860 |
"robotics.robotics-reinforcement-learning": {
|
| 5861 |
"query": "\"robotics reinforcement learning\" in:description",
|
| 5862 |
"years": [
|
| 5863 |
2026,
|
| 5864 |
+
2025,
|
| 5865 |
+
2024
|
| 5866 |
]
|
| 5867 |
},
|
| 5868 |
"robotics.robotics-topic": {
|
| 5869 |
"query": "topic:robotics",
|
| 5870 |
"years": [
|
| 5871 |
2026,
|
| 5872 |
+
2025,
|
| 5873 |
+
2024
|
| 5874 |
]
|
| 5875 |
},
|
| 5876 |
"robotics.sim2real": {
|
| 5877 |
"query": "\"sim-to-real\" in:description",
|
| 5878 |
"years": [
|
| 5879 |
2026,
|
| 5880 |
+
2025,
|
| 5881 |
+
2024
|
| 5882 |
]
|
| 5883 |
},
|
| 5884 |
"robotics.slam": {
|
| 5885 |
"query": "SLAM robotics in:description",
|
| 5886 |
"years": [
|
| 5887 |
2026,
|
| 5888 |
+
2025,
|
| 5889 |
+
2024
|
| 5890 |
]
|
| 5891 |
},
|
| 5892 |
"robotics.tactile-learning": {
|
|
|
|
| 5985 |
"query": "fusion plasma in:description \"machine learning\"",
|
| 5986 |
"years": [
|
| 5987 |
2026,
|
| 5988 |
+
2025,
|
| 5989 |
+
2024
|
| 5990 |
]
|
| 5991 |
},
|
| 5992 |
"science.gravitational-waves": {
|
| 5993 |
"query": "\"gravitational wave\" \"machine learning\" in:description,readme",
|
| 5994 |
"years": [
|
| 5995 |
2026,
|
| 5996 |
+
2025,
|
| 5997 |
+
2024
|
| 5998 |
]
|
| 5999 |
},
|
| 6000 |
"science.inverse-problems": {
|
| 6001 |
"query": "\"inverse problems\" in:description",
|
| 6002 |
"years": [
|
| 6003 |
2026,
|
| 6004 |
+
2025,
|
| 6005 |
+
2024
|
| 6006 |
]
|
| 6007 |
},
|
| 6008 |
"science.neural-operators": {
|
| 6009 |
"query": "\"neural operator\" in:description",
|
| 6010 |
"years": [
|
| 6011 |
2026,
|
| 6012 |
+
2025,
|
| 6013 |
+
2024
|
| 6014 |
]
|
| 6015 |
},
|
| 6016 |
"science.ocean-modeling": {
|
| 6017 |
"query": "\"ocean modeling\" \"machine learning\" in:description,readme",
|
| 6018 |
"years": [
|
| 6019 |
2026,
|
| 6020 |
+
2025,
|
| 6021 |
+
2024
|
| 6022 |
]
|
| 6023 |
},
|
| 6024 |
"science.particle-physics": {
|
| 6025 |
"query": "\"particle physics\" in:description",
|
| 6026 |
"years": [
|
| 6027 |
2026,
|
| 6028 |
+
2025,
|
| 6029 |
+
2024
|
| 6030 |
]
|
| 6031 |
},
|
| 6032 |
"science.photonics": {
|
| 6033 |
"query": "photonics \"machine learning\" in:description,readme",
|
| 6034 |
"years": [
|
| 6035 |
2026,
|
| 6036 |
+
2025,
|
| 6037 |
+
2024
|
| 6038 |
]
|
| 6039 |
},
|
| 6040 |
"science.physics": {
|
| 6041 |
"query": "physics in:description",
|
| 6042 |
"years": [
|
| 6043 |
2026,
|
| 6044 |
+
2025,
|
| 6045 |
+
2024
|
| 6046 |
]
|
| 6047 |
},
|
| 6048 |
"science.physics-informed-neural-networks": {
|
| 6049 |
"query": "\"physics-informed neural network\" in:description",
|
| 6050 |
"years": [
|
| 6051 |
2026,
|
| 6052 |
+
2025,
|
| 6053 |
+
2024
|
| 6054 |
]
|
| 6055 |
},
|
| 6056 |
"science.plasma-physics": {
|
| 6057 |
"query": "\"plasma physics\" in:description",
|
| 6058 |
"years": [
|
| 6059 |
2026,
|
| 6060 |
+
2025,
|
| 6061 |
+
2024
|
| 6062 |
]
|
| 6063 |
},
|
| 6064 |
"science.quantum-materials": {
|
| 6065 |
"query": "\"quantum materials\" \"machine learning\" in:description,readme",
|
| 6066 |
"years": [
|
| 6067 |
2026,
|
| 6068 |
+
2025,
|
| 6069 |
+
2024
|
| 6070 |
]
|
| 6071 |
},
|
| 6072 |
"science.quantum-physics": {
|
|
|
|
| 6186 |
"query": "\"fMRI decoding\" \"machine learning\" in:description,readme",
|
| 6187 |
"years": [
|
| 6188 |
2026,
|
| 6189 |
+
2025,
|
| 6190 |
+
2024
|
| 6191 |
]
|
| 6192 |
},
|
| 6193 |
"specialized.machine-unlearning": {
|
| 6194 |
"query": "\"machine unlearning\" in:description,readme",
|
| 6195 |
"years": [
|
| 6196 |
2026,
|
| 6197 |
+
2025,
|
| 6198 |
+
2024
|
| 6199 |
]
|
| 6200 |
},
|
| 6201 |
"specialized.mechanistic-interpretability": {
|
| 6202 |
"query": "\"mechanistic interpretability\" in:description,readme",
|
| 6203 |
"years": [
|
| 6204 |
2026,
|
| 6205 |
+
2025,
|
| 6206 |
+
2024
|
| 6207 |
]
|
| 6208 |
},
|
| 6209 |
"specialized.medical-image-registration-deep-learning": {
|
| 6210 |
"query": "\"medical image registration\" \"deep learning\" in:description,readme",
|
| 6211 |
"years": [
|
| 6212 |
2026,
|
| 6213 |
+
2025,
|
| 6214 |
+
2024
|
| 6215 |
]
|
| 6216 |
},
|
| 6217 |
"specialized.pathology-foundation-model": {
|
| 6218 |
"query": "\"pathology foundation model\" \"machine learning\" in:description,readme",
|
| 6219 |
"years": [
|
| 6220 |
2026,
|
| 6221 |
+
2025,
|
| 6222 |
+
2024
|
| 6223 |
]
|
| 6224 |
},
|
| 6225 |
"specialized.spiking-neural-network": {
|
| 6226 |
"query": "\"spiking neural network\" in:description,readme",
|
| 6227 |
"years": [
|
| 6228 |
2026,
|
| 6229 |
+
2025,
|
| 6230 |
+
2024
|
| 6231 |
]
|
| 6232 |
},
|
| 6233 |
"specialized.test-time-adaptation": {
|
| 6234 |
"query": "\"test-time adaptation\" in:description,readme",
|
| 6235 |
"years": [
|
| 6236 |
2026,
|
| 6237 |
+
2025,
|
| 6238 |
+
2024
|
| 6239 |
]
|
| 6240 |
},
|
| 6241 |
"timeseries.anomaly-detection": {
|
|
|
|
| 6306 |
"query": "\"long horizon forecasting\" in:readme",
|
| 6307 |
"years": [
|
| 6308 |
2026,
|
| 6309 |
+
2025,
|
| 6310 |
+
2024
|
| 6311 |
]
|
| 6312 |
},
|
| 6313 |
"timeseries.multivariate": {
|
| 6314 |
"query": "\"multivariate time series\" in:description",
|
| 6315 |
"years": [
|
| 6316 |
2026,
|
| 6317 |
+
2025,
|
| 6318 |
+
2024
|
| 6319 |
]
|
| 6320 |
},
|
| 6321 |
"timeseries.nbeats": {
|
| 6322 |
"query": "N-BEATS in:description",
|
| 6323 |
"years": [
|
| 6324 |
2026,
|
| 6325 |
+
2025,
|
| 6326 |
+
2024
|
| 6327 |
]
|
| 6328 |
},
|
| 6329 |
"timeseries.patchtst": {
|
| 6330 |
"query": "PatchTST in:description",
|
| 6331 |
"years": [
|
| 6332 |
2026,
|
| 6333 |
+
2025,
|
| 6334 |
+
2024
|
| 6335 |
]
|
| 6336 |
},
|
| 6337 |
"timeseries.predictive-maintenance": {
|
| 6338 |
"query": "\"predictive maintenance\" in:description",
|
| 6339 |
"years": [
|
| 6340 |
2026,
|
| 6341 |
+
2025,
|
| 6342 |
+
2024
|
| 6343 |
]
|
| 6344 |
},
|
| 6345 |
"timeseries.probabilistic-forecasting": {
|
| 6346 |
"query": "\"probabilistic forecasting\" in:readme",
|
| 6347 |
"years": [
|
| 6348 |
2026,
|
| 6349 |
+
2025,
|
| 6350 |
+
2024
|
| 6351 |
]
|
| 6352 |
},
|
| 6353 |
"timeseries.remaining-useful-life": {
|
| 6354 |
"query": "\"remaining useful life\" in:readme",
|
| 6355 |
"years": [
|
| 6356 |
2026,
|
| 6357 |
+
2025,
|
| 6358 |
+
2024
|
| 6359 |
]
|
| 6360 |
},
|
| 6361 |
"timeseries.sensor-data": {
|
| 6362 |
"query": "\"sensor time series\" in:description",
|
| 6363 |
"years": [
|
| 6364 |
2026,
|
| 6365 |
+
2025,
|
| 6366 |
+
2024
|
| 6367 |
]
|
| 6368 |
},
|
| 6369 |
"timeseries.state-space-models": {
|
| 6370 |
"query": "\"state space model\" in:description",
|
| 6371 |
"years": [
|
| 6372 |
2026,
|
| 6373 |
+
2025,
|
| 6374 |
+
2024
|
| 6375 |
]
|
| 6376 |
},
|
| 6377 |
"timeseries.streaming": {
|
| 6378 |
"query": "\"streaming time series\" in:readme",
|
| 6379 |
"years": [
|
| 6380 |
2026,
|
| 6381 |
+
2025,
|
| 6382 |
+
2024
|
| 6383 |
]
|
| 6384 |
},
|
| 6385 |
"timeseries.synthetic-generation": {
|
| 6386 |
"query": "\"time series generation\" in:description,readme",
|
| 6387 |
"years": [
|
| 6388 |
2026,
|
| 6389 |
+
2025,
|
| 6390 |
+
2024
|
| 6391 |
]
|
| 6392 |
},
|
| 6393 |
"timeseries.tabular-foundation-models": {
|
|
|
|
| 6507 |
"query": "\"causal machine learning\" in:description",
|
| 6508 |
"years": [
|
| 6509 |
2026,
|
| 6510 |
+
2025,
|
| 6511 |
+
2024
|
| 6512 |
]
|
| 6513 |
},
|
| 6514 |
"trust.causal-representation-learning": {
|
| 6515 |
"query": "\"causal representation learning\" in:description",
|
| 6516 |
"years": [
|
| 6517 |
2026,
|
| 6518 |
+
2025,
|
| 6519 |
+
2024
|
| 6520 |
]
|
| 6521 |
},
|
| 6522 |
"trust.conformal-prediction": {
|
| 6523 |
"query": "\"conformal prediction\" in:description",
|
| 6524 |
"years": [
|
| 6525 |
2026,
|
| 6526 |
+
2025,
|
| 6527 |
+
2024
|
| 6528 |
]
|
| 6529 |
},
|
| 6530 |
"trust.counterfactual-explanations": {
|
| 6531 |
"query": "\"counterfactual explanation\" in:description",
|
| 6532 |
"years": [
|
| 6533 |
2026,
|
| 6534 |
+
2025,
|
| 6535 |
+
2024
|
| 6536 |
]
|
| 6537 |
},
|
| 6538 |
"trust.differential-privacy": {
|
| 6539 |
"query": "\"differential privacy\" in:description",
|
| 6540 |
"years": [
|
| 6541 |
2026,
|
| 6542 |
+
2025,
|
| 6543 |
+
2024
|
| 6544 |
]
|
| 6545 |
},
|
| 6546 |
"trust.distribution-shift": {
|
| 6547 |
"query": "\"distribution shift\" in:description",
|
| 6548 |
"years": [
|
| 6549 |
2026,
|
| 6550 |
+
2025,
|
| 6551 |
+
2024
|
| 6552 |
]
|
| 6553 |
},
|
| 6554 |
"trust.domain-generalization": {
|
| 6555 |
"query": "\"domain generalization\" in:description",
|
| 6556 |
"years": [
|
| 6557 |
2026,
|
| 6558 |
+
2025,
|
| 6559 |
+
2024
|
| 6560 |
]
|
| 6561 |
},
|
| 6562 |
"trust.explainable-ai": {
|
| 6563 |
"query": "\"explainable AI\" in:description",
|
| 6564 |
"years": [
|
| 6565 |
2026,
|
| 6566 |
+
2025,
|
| 6567 |
+
2024
|
| 6568 |
]
|
| 6569 |
},
|
| 6570 |
"trust.federated-learning": {
|
| 6571 |
"query": "\"federated learning\" in:description",
|
| 6572 |
"years": [
|
| 6573 |
2026,
|
| 6574 |
+
2025,
|
| 6575 |
+
2024
|
| 6576 |
]
|
| 6577 |
},
|
| 6578 |
"trust.instrumental-variable-ml": {
|
| 6579 |
"query": "\"double machine learning\" in:description",
|
| 6580 |
"years": [
|
| 6581 |
2026,
|
| 6582 |
+
2025,
|
| 6583 |
+
2024
|
| 6584 |
]
|
| 6585 |
},
|
| 6586 |
"trust.interpretable-ml": {
|
| 6587 |
"query": "\"interpretable machine learning\" in:description",
|
| 6588 |
"years": [
|
| 6589 |
2026,
|
| 6590 |
+
2025,
|
| 6591 |
+
2024
|
| 6592 |
]
|
| 6593 |
},
|
| 6594 |
"trust.membership-inference": {
|
|
|
|
| 6729 |
"query": "\"image retrieval\" in:readme",
|
| 6730 |
"years": [
|
| 6731 |
2026,
|
| 6732 |
+
2025,
|
| 6733 |
+
2024
|
| 6734 |
]
|
| 6735 |
},
|
| 6736 |
"vision.image-super-resolution": {
|
| 6737 |
"query": "\"image super-resolution\" in:readme",
|
| 6738 |
"years": [
|
| 6739 |
2026,
|
| 6740 |
+
2025,
|
| 6741 |
+
2024
|
| 6742 |
]
|
| 6743 |
},
|
| 6744 |
"vision.image-to-image-translation": {
|
| 6745 |
"query": "\"image-to-image translation\" in:readme",
|
| 6746 |
"years": [
|
| 6747 |
2026,
|
| 6748 |
+
2025,
|
| 6749 |
+
2024
|
| 6750 |
]
|
| 6751 |
},
|
| 6752 |
"vision.neural-rendering": {
|
| 6753 |
"query": "\"neural rendering\" in:description",
|
| 6754 |
"years": [
|
| 6755 |
2026,
|
| 6756 |
+
2025,
|
| 6757 |
+
2024
|
| 6758 |
]
|
| 6759 |
},
|
| 6760 |
"vision.object-detection": {
|
| 6761 |
"query": "\"object detection\" in:description",
|
| 6762 |
"years": [
|
| 6763 |
2026,
|
| 6764 |
+
2025,
|
| 6765 |
+
2024
|
| 6766 |
]
|
| 6767 |
},
|
| 6768 |
"vision.object-tracking": {
|
| 6769 |
"query": "\"object tracking\" in:readme",
|
| 6770 |
"years": [
|
| 6771 |
2026,
|
| 6772 |
+
2025,
|
| 6773 |
+
2024
|
| 6774 |
]
|
| 6775 |
},
|
| 6776 |
"vision.ocr": {
|
| 6777 |
"query": "topic:ocr",
|
| 6778 |
"years": [
|
| 6779 |
2026,
|
| 6780 |
+
2025,
|
| 6781 |
+
2024
|
| 6782 |
]
|
| 6783 |
},
|
| 6784 |
"vision.open-vocabulary-detection": {
|
| 6785 |
"query": "\"open-vocabulary detection\" in:readme",
|
| 6786 |
"years": [
|
| 6787 |
2026,
|
| 6788 |
+
2025,
|
| 6789 |
+
2024
|
| 6790 |
]
|
| 6791 |
},
|
| 6792 |
"vision.optical-flow": {
|
| 6793 |
"query": "topic:optical-flow",
|
| 6794 |
"years": [
|
| 6795 |
2026,
|
| 6796 |
+
2025,
|
| 6797 |
+
2024
|
| 6798 |
]
|
| 6799 |
},
|
| 6800 |
"vision.pose-estimation": {
|
| 6801 |
"query": "\"human pose estimation\" in:readme",
|
| 6802 |
"years": [
|
| 6803 |
2026,
|
| 6804 |
+
2025,
|
| 6805 |
+
2024
|
| 6806 |
]
|
| 6807 |
},
|
| 6808 |
"vision.promptable-segmentation": {
|
| 6809 |
"query": "\"promptable segmentation\" in:readme",
|
| 6810 |
"years": [
|
| 6811 |
2026,
|
| 6812 |
+
2025,
|
| 6813 |
+
2024
|
| 6814 |
]
|
| 6815 |
},
|
| 6816 |
"vision.segmentation": {
|
|
|
|
| 6879 |
"end": "2026-09-24",
|
| 6880 |
"search_policy_version": 2,
|
| 6881 |
"start_year": 2008,
|
| 6882 |
+
"updated_at": "2026-10-01T17:35:19Z"
|
| 6883 |
}
|