TabPFN outperforms published models on three energetic-material properties
Untuned TabPFN on Chemprop embeddings beats Chemprop itself and is more than ten times faster than XGBoost.
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Untuned TabPFN on Chemprop embeddings beats Chemprop itself and is more than ten times faster than XGBoost.
Pretrained in-context quantile regression beats feasible generalized least squares, especially when causes are multivariate.
Across 512 held-out worlds, complete-edit F1 rose from 0.016 with no executions to 0.685 with 64.
Audits of 10 classifiers on BRFSS show target leakage, not model class, drives the reported 0.89 AUROC in survey-based cardiovascular screening.
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