GraphVAMPNet, using graph neural networks and variational approach to Markov processes for dynamical modeling of biomolecules

Research article (The Journal of Chemical Physics, 2022) · cited 48× · AI/ML
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GraphVAMPNet, using graph neural networks and variational approach to Markov processes for dynamical modeling of biomolecules

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GraphVAMPNet, using graph neural networks and variational approach to Markov processes for dynamical modeling of biomolecules is a scholarly article[1].

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APA 4ort.xyz Knowledge Graph. (2026). GraphVAMPNet, using graph neural networks and variational approach to Markov processes for dynamical modeling of biomolecules. Retrieved May 24, 2026, from https://4ort.xyz/entity/graphvampnet-using-graph-neural-networks-and-variational-approach-to-markov-processes-for-dynamical-modeling-of-biomolec
MLA “GraphVAMPNet, using graph neural networks and variational approach to Markov processes for dynamical modeling of biomolecules.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/graphvampnet-using-graph-neural-networks-and-variational-approach-to-markov-processes-for-dynamical-modeling-of-biomolec.
BibTeX @misc{4ortxyz_graphvampnet-using-graph-neural-networks-and-variational-approach-to-markov-processes-for-dynamical-modeling-of-biomolec_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{GraphVAMPNet, using graph neural networks and variational approach to Markov processes for dynamical modeling of biomolecules}}, year = {2026}, url = {https://4ort.xyz/entity/graphvampnet-using-graph-neural-networks-and-variational-approach-to-markov-processes-for-dynamical-modeling-of-biomolec}, note = {Accessed: 2026-05-24}}
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