112 citations · 237 across the 19 of their papers we have counts for
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physics.chem-ph2021★ 112 cited
Learning neural network potentials from experimental data via Differentiable Trajectory Reweighting
Stephan Thaler, Julija Zavadlav
In molecular dynamics (MD), neural network (NN) potentials trained bottom-up on quantum mechanical data have seen tremendous success recently. Top-down approaches that learn NN pot…
physics.comp-ph2021
Accelerated Simulations of Molecular Systems through Learning of their Effective Dynamics
Pantelis R. Vlachas, Julija Zavadlav, Matej Praprotnik +1
Simulations are vital for understanding and predicting the evolution of complex molecular systems. However, despite advances in algorithms and special purpose hardware, accessing t…