Datasets:
Formats:
csv
Languages:
English
Size:
< 1K
Tags:
continual-learning
catastrophic-forgetting
functional-memory
orthogonal-projection
statistical-certification
pytorch
| { | |
| "scope": "Independent recomputation of reported mean/SD/t95 and paired t95 intervals from fully audited saved-prediction per-run values", | |
| "prediction_audit_sha256": "10b9677525b6b338aa0a0078929ec6be4444d6e5e4360ba17c1305a97214892a", | |
| "aggregate_sha256": "80b21c84e01436fd8942bf82de66e3b3eda8ff204de0d65b0c1795a29d000582", | |
| "source_lock_sha256": "af4ac3635681ac02faa2b36181830f45654c3f9549601258e2fe4aa879308825", | |
| "completed_runs": 260, | |
| "group_count": 26, | |
| "numeric_values_checked": 1561, | |
| "maximum_absolute_discrepancy": 3.3306690738754696e-16, | |
| "all_passed": true, | |
| "failures": [], | |
| "not_checked": "Runtime-derived timing/RSS/payload interval accuracy is not part of this prediction-statistics check; no multiplicity-adjusted inference is asserted." | |
| } | |