Explainable TabNet model predicts workforce performance scores in benchmark dataset
An explainable TabNet framework achieved an R² of 0.9880 when predicting employee performance from 100,000 workforce records, while its authors ...
An explainable TabNet framework achieved an R² of 0.9880 when predicting employee performance from 100,000 workforce records, while its authors ...
A systematic review finds hybrid CNN-transformer models lead stroke lesion analysis, but explainable AI appears in only 11 percent of ...
A controlled study of 1,196 coffee leaf images found that an explainable Vision Transformer classified nutrient deficiencies with up to ...
A district-scale study in Somalia combined satellite validation, 14 conditioning factors and ensemble machine learning to map flood susceptibility across ...
A hybrid DeiT system reached 99.13% accuracy on a 38-class plant disease benchmark while combining local and global AI explanations ...
An ensemble of LSTM and CatBoost predicts one-year-ahead city-level methane emissions, with urban ecological and environmental quality showing the strongest ...
A new neural architecture converts the classical Volterra series into learnable coefficient tensors, recovering known chaotic dynamics, matching transformer physics, ...
A proof-of-concept study fused EEG recordings with clinical interview transcripts from 520 participants, achieving near-ceiling accuracy under controlled conditions while ...
A 79,717-parameter attention-fused neural network called LeafXNet matches or beats far larger deep learning models at detecting watermelon, grape, and ...
A retrospective analysis of 1,101 serum samples used explainable artificial intelligence to prioritize circulating microRNAs that distinguished pancreatic cancer from ...
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© 2025 Scienmag - Science Magazine