Publication: DeepCV: A Deep Learning Framework for Blind Search of Collective Variables in Expanded Configurational Space
DeepCV: A Deep Learning Framework for Blind Search of Collective Variables in Expanded Configurational Space
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Ketkaew, R., & Luber, S. (2022). DeepCV: A Deep Learning Framework for Blind Search of Collective Variables in Expanded Configurational Space. Journal of Chemical Information and Modeling, 62(24), 6352–6364. https://doi.org/10.1021/acs.jcim.2c00883
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We present Deep learning for Collective Variables (DeepCV), a computer code that provides an efficient and customizable implementation of the deep autoencoder neural network (DAENN) algorithm that has been developed in our group for computing collective variables (CVs) and can be used with enhanced sampling methods to reconstruct free energy surfaces of chemical reactions. DeepCV can be used to conveniently calculate molecular features, train models, generate CVs, validate rare events from sampling, and analyze a trajectory for chemic
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- Luber, Sandra
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Ketkaew, R., & Luber, S. (2022). DeepCV: A Deep Learning Framework for Blind Search of Collective Variables in Expanded Configurational Space. Journal of Chemical Information and Modeling, 62(24), 6352–6364. https://doi.org/10.1021/acs.jcim.2c00883
