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physics.chem-ph2026
Simulation-Supervised Foundation Models for Retention Time Prediction in High-Performance Liquid Chromatography beyond Experimental Data Coverage
Stephen Wu, Yufeng Han, Yasuhiro Mito +5
Accurate prediction of high-performance liquid chromatography (HPLC) retention times (RTs) across diverse molecules and chromatographic methods remains challenging because experime…
cs.CE2026
TabPFN Extensions for Interpretable Geotechnical Modelling
Taiga Saito, Yu Otake, Daijiro Mizutani +1
Geotechnical site characterisation relies on sparse, heterogeneous borehole data, where uncertainty quantification and interpretability matter as much as predictive accuracy. We ev…