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Implicit Transfer Operator Learning: Multiple Time-Resolution Surrogates for Molecular Dynamics
Computing properties of molecular systems rely on estimating expectations of the (unnormalized) Boltzmann distribution.
Transition1x -- a Dataset for Building Generalizable Reactive Machine Learning Potentials
In this work, we present the dataset Transition1x containing 9. 6 million Density Functional Theory (DFT) calculations of forces and energies of molecular configurations on and around reaction pathways at the wB97x/6-31G(d) level of theory.
NeuralNEB -- Neural Networks can find Reaction Paths Fast
We also compare with and outperform Density Functional based Tight Binding (DFTB) on both accuracy and computational resource.
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