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cs.LG2026
Derivative Informed Learning of Exchange-Correlation Functionals
Eike S. Eberhard, Luca A. Thiede, Abdul Aldossary +5
Machine-learned (ML) exchange-correlation (XC) functionals aim to replace human-designed density functional approximations by learning directly from reference data, but they still…
cs.LG2026
Excited Pfaffians: Generalized Neural Wave Functions Across Structure and State
Nicholas Gao, Till Grutschus, Frank Noé +1
Neural-network wave functions in Variational Monte Carlo (VMC) have achieved great success in accurately representing both ground and excited states. However, achieving sufficient…