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jgalego
/
orbit2vec

Feature Extraction
PyTorch
Safetensors
space
satellites
tle
embeddings
contrastive-learning
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orbit2vec
File size: 1,384 Bytes
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{
  "depth": 4,
  "dim": 256,
  "embed_dim": 256,
  "feature_mean": [
    0.2595488131046295,
    0.008254659362137318,
    -6.003311634063721,
    0.7771091461181641,
    0.009001758880913258,
    0.01654639281332493,
    0.028064265847206116,
    0.07831894606351852,
    0.020051907747983932,
    1.619292140007019,
    1.5279791355133057
  ],
  "feature_std": [
    0.4458872973918915,
    1.1697551012039185,
    2.424814224243164,
    0.3001880347728729,
    0.44748619198799133,
    0.7060166597366333,
    0.7074488997459412,
    0.7716799974441528,
    0.6308556795120239,
    2.0706324577331543,
    2.3363101482391357
  ],
  "groups": [
    "COSMOS",
    "FLOCK",
    "GLOBALSTAR",
    "HULIANWANG",
    "ICEYE",
    "INTELSAT",
    "IRIDIUM",
    "JILIN",
    "KUIPER",
    "LEMUR",
    "METEOR",
    "MOLNIYA",
    "NAVSTAR",
    "ONEWEB",
    "OPS",
    "PROGRESS",
    "QIANFAN",
    "SOYUZ",
    "SPACEBEE",
    "STARLINK",
    "STS",
    "TRANSPORTER",
    "USA",
    "YAOGAN",
    "debris",
    "other payload",
    "rocket body",
    "unknown"
  ],
  "heads": 8,
  "owners": [
    "CIS",
    "ESA",
    "FR",
    "GER",
    "IND",
    "IT",
    "ITSO",
    "JPN",
    "PRC",
    "TBD",
    "UK",
    "US",
    "other"
  ],
  "target_mean": [
    70.28289794921875,
    -0.09830036759376526
  ],
  "target_std": [
    27.541488647460938,
    0.5646975636482239
  ]
}