Charting electronic-state manifolds across molecules with multi-state learning and gap-driven dynamics via efficient and robust active learning
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We present a robust protocol for affordable learning of electronic states to accelerate photophysical and photochemical molecular simulations. The protocol solves several issues precluding the widespread use of machine learning (ML) in excited-state simulation... ...
