Frontiers in AI in Theoretical Chemistry

Monday, November 20, 2023

9:00am to 4:00pm

Beckman Behavioral Biology B180

Frank Noé, Advancing Physical and Theoretical Chemistry with Deep Learning,

David Limmer, Variational Deep Learning of Transition Path Ensembles In and Out of Equilibrium,

Michele Ceriotti, Machine-learning Representations, Beyond Locality,

Pratyush Tiwary, From Chemical Identity to Boltzmann Ensembles for Proteins, RNA and Crystals with Generative AI and Statistical Mechanics,

Erik Thiede, Inferring the Distribution of Biomolecular Conformations from CryoEM,

Gábor Csányi, The MACE Force Field Architecture,

Grant Rotskoff, Thermodynamically Consistent, Scalable Back-Mapping with Generative Neural Networks,

Cecilia Clementi,

Boris Kozinksy,

For more information, please contact Aracely Sustaita by phone at x3654 or by email at [email protected].

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