All-in-one: Learning across quantum chemical levels. Better than transfer learning!

Here, we propose the all-in-one (AIO) ANI model, which is able to handle an arbitrary number of QC levels.

JOC: Surprising dynamics phenomena in the Diels–Alder reaction of C60 uncovered with AI

Recently, we published a paper in JOC about the surprising dynamics phenomena in the Diels–Alder reaction of fullerene C60.

AIQM2 is out: better and faster than B3LYP for reaction simulations!

AIQM2 is the long-awaited successor of the highly successful AIQM1.

Physically consistent simulation of quantum dissipative dynamics with neural networks

Physics-Informed Neural Networks and Beyond: Enforcing Physical Constraints in Quantum Dissipative Dynamics

JCTC: Physics-informed active learning for accelerating quantum chemical simulations

It shortens molecular simulation time to a couple of days which could have taken weeks of pure quantum chemical calculations.

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