When Active Learning Fails, Uncalibrated Out of Distribution Uncertainty Quantification Might Be the Problem Data and Model Artifacts
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Model checkpoints and result artifacts supporting the paper \"When Active Learning Fails, Uncalibrated Out of Distribution Uncertainty Quantification Might Be the Problem\" (arXiv:2511.17760). Includes ALIGNN ensemble checkpoints, loss-landscape sampling results, active-learning experiment histories, and the featurized JARVIS-22 dataset used for training.
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Zenodo创建时间：
2026-06-22
