VAC (Variational approach for conformation dynamics)

Paper

• Noé, Frank, and Feliks Nuske. “A variational approach to modeling slow processes in stochastic dynamical systems.” Multiscale Modeling & Simulation 11.2 (2013): 635-655. [BibTex]

Code

• origin : markovmodel/variational
• forked : tanaka-hiroki1989/variational
• package : markovmodel/PyEMMA

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VAMP (Variational approach for Marokov process)

Paper

• Wu, Hao, and Frank Noé. “Variational approach for learning Markov processes from time series data.” Journal of Nonlinear Science 30.1 (2020): 23-66.

Code

• pacakge :markovmodel/PyEMMA

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VAMPnets

Paper

• Mardt, Andreas, et al. “VAMPnets for deep learning of molecular kinetics.” Nature communications 9.1 (2018): 1-11. [BibTex]

Code

• origin markovmodel/deeptime
• forked tanaka-hiroki1989/deeptime
• example tanaka-hiroki1989/vampnets_ex

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SRV (state-free reversible

Paper

• Chen, Wei, Hythem Sidky, and Andrew L. Ferguson. “Nonlinear discovery of slow molecular modes using state-free reversible VAMPnets.” The Journal of chemical physics 150.21 (2019): 214114.[BibTex]

Code

• origin hsidky/srv

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Molecular latent space simulator

Paper

• Sidky, Hythem, Wei Chen, and Andrew L. Ferguson. “Molecular latent space simulators.” Chemical Science 11.35 (2020): 9459-9467.

Code

• hsidky/srv/tree/newgen

[detail])

GDynet (Graph dynamical netowrks)

Paper

• Xie, T., France-Lanord, A., Wang, Y. et al. Graph dynamical networks for unsupervised learning of atomic scale dynamics in materials. Nat Commun 10, 2667 (2019))[BibTex]

Code

• origin txie-93/gdynet

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RPnet (Reverse projection based neural network)

Paper

• Gu, Hanlin, et al. “RPnet: a reverse-projection-based neural network for coarse-graining metastable conformational states for protein dynamics.” Physical Chemistry Chemical Physics (2022).[BibTex]

Code

• origin ghl1995/BpNet-limping

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GraphVAMPnet

Paper

• GraphVAMPNet, using graph neural networks and variational approach to markov processes for dynamical modeling of biomolecules [BibTex]

Code

• origin ghorbanimahdi73/GraphVampnet

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DeepGenMSM

Paper

• Wu, Hao, et al. “Deep generative markov state models.” Advances in Neural Information Processing Systems 31 (2018)

Code

• amardt/DeepGenMSM

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DeepRevMSM

Paper

• Mardt, Andreas, et al. “Deep learning Markov and Koopman models with physical constraints.” Mathematical and Scientific Machine Learning. PMLR, 2020.

Code

• origin markovmodel/deep_rev_msm
• forked tanaka-hiroki1989/deep_rev_msm

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iVAMPnets (independent Markov decomposition with VAMPnets)

Paper

• Preprint Deep learning to decompose macromolecules into independent Markovian domains

  Code

• origin markovmodel/ivampnets
• forked tanaka-hiroki1989/ivampnets

Galerkin approximation

Paper

• https://aip.scitation.org/doi/10.1063/1.5063730