Machine learning models using smartwatch data from a 54-participant test-track study detect alcohol-impaired driving with participant-averaged AUROC of 0.88 for any intoxication and 0.86 above 0.05 g/dL.
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A causal machine-learning model using variability features from Fermi-LAT light curves predicts blazar flare activity within 90 days with 86% recall on held-out data for one FSRQ.
OOD-SEG reframes multi-class segmentation from sparse positive-only annotations as pixel-wise positive-unlabelled learning solved by integrating out-of-distribution detection techniques, with a proposed cross-validation evaluation on surgical imaging datasets.
Gated SAEs decouple which features to use from how large their activations should be, applying the L1 penalty only to selection and thereby eliminating shrinkage while halving the number of firing features needed for good fidelity.
PG-TMT couples a physics-aligned tri-branch encoder with EVT-calibrated decision rules to achieve higher PR-AUC and shorter detection times at controlled false-alarm rates across multiple bearing datasets.
Video forgeries are detectable via binary classification on multimedia stream descriptors without pixel analysis.
The paper establishes a reproducible retrospective benchmark for ranking daily active-fire detections in Cerrado conservation units by comparing atmospheric, surface, static spatial, and short-term memory covariates with standard ML models under time-series cross-validation and held-out AOI tests.
BioBLP is a modular embedding framework for multimodal biomedical KGs supporting heterogeneous attributes and missing data, with a pretraining strategy that improves results on drug-protein interaction prediction especially for low-degree entities.
Normalized velocity descriptors from facial keypoints with Random Forest yield 0.826 balanced accuracy and 0.855 AUROC on YouTubePD video classification, stable across 10 seeds with region ablation and permutation importance.
STR-Net achieves AUROC of 0.933 for binary bone-loss screening and 0.801 correlation for T-score estimation from knee X-rays on a held-out test set.
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