252 citations · 433 across the 25 of their papers we have counts for
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Interpretable Embeddings From Molecular Simulations Using Gaussian Mixture Variational Autoencoders
Yasemin Bozkurt Varolgunes, Tristan Bereau, Joseph F. Rudzinski
Extracting insight from the enormous quantity of data generated from molecular simulations requires the identification of a small number of collective variables whose corresponding…
Direct route to reproducing pair distribution functions with coarse-grained models via transformed atomistic cross correlations
Svenja J. Woerner, Tristan Bereau, Kurt Kremer +1
Coarse-grained (CG) models are often parametrized to reproduce one-dimensional structural correlation functions of an atomically-detailed model along the degrees of freedom governi…
Microscopic reweighting for non-equilibrium steady states dynamics
Marius Bause, Timon Wittenstein, Kurt Kremer +1
Computer simulations generate trajectories at a single, well-defined thermodynamic state point. Statistical reweighting offers the means to reweight static and dynamical properties…
Resolution limit of data-driven coarse-grained models spanning chemical space
Kiran H. Kanekal, Tristan Bereau
Increasing the efficiency of materials design and discovery remains a significant challenge, especially given the prohibitively large size of chemical compound space. The use of a…
Controlled exploration of chemical space by machine learning of coarse-grained representations
Christian Hoffmann, Roberto Menichetti, Kiran H. Kanekal +1
The size of chemical compound space is too large to be probed exhaustively. This leads high-throughput protocols to drastically subsample and results in sparse and non-uniform data…