3 citations · 4 across the 2 of their papers we have counts for
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Utilizing Machine Learning to Greatly Expand the Range and Accuracy of Bottom-Up Coarse-Grained Models Through Virtual Particles
Patrick G. Sahrmann, Timothy D. Loose, Aleksander E. P. Durumeric +1
Coarse-grained (CG) models parameterized using atomistic reference data, i.e., 'bottom up' CG models, have proven useful in the study of biomolecules and other soft matter. However…
Explaining classifiers to understand coarse-grained models
Aleksander Evren Paetzold Durumeric, Gregory A. Voth
Bottom-up coarse-grained molecular dynamics models are parameterized using complex effective Hamiltonians. These models are typically optimized to approximate high dimensional data…
Adversarial-Residual-Coarse-Graining: Applying machine learning theory to systematic molecular coarse-graining
Aleksander E. P. Durumeric, Gregory A. Voth
We utilize connections between molecular coarse-graining approaches and implicit generative models in machine learning to describe a new framework for systematic molecular coarse-g…