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Note: Variational Encoding of Protein Dynamics Benefits from Maximizing
  Latent Autocorrelation

Note: Variational Encoding of Protein Dynamics Benefits from Maximizing Latent Autocorrelation

17 March 2018
H. Wayment-Steele
Vijay S. Pande
    DRL
ArXivPDFHTML

Papers citing "Note: Variational Encoding of Protein Dynamics Benefits from Maximizing Latent Autocorrelation"

4 / 4 papers shown
Title
DeepDriveMD: Deep-Learning Driven Adaptive Molecular Simulations for
  Protein Folding
DeepDriveMD: Deep-Learning Driven Adaptive Molecular Simulations for Protein Folding
Hyungro Lee
Heng Ma
Matteo Turilli
D. Bhowmik
S. Jha
A. Ramanathan
AI4CE
6
70
0
17 Sep 2019
Capabilities and Limitations of Time-lagged Autoencoders for Slow Mode
  Discovery in Dynamical Systems
Capabilities and Limitations of Time-lagged Autoencoders for Slow Mode Discovery in Dynamical Systems
Wei Chen
Hythem Sidky
Andrew L. Ferguson
33
36
0
02 Jun 2019
Variational Encoding of Complex Dynamics
Variational Encoding of Complex Dynamics
Carlos X. Hernández
H. Wayment-Steele
Mohammad M. Sultan
B. Husic
Vijay S. Pande
AI4CE
33
138
0
23 Nov 2017
Time-lagged autoencoders: Deep learning of slow collective variables for
  molecular kinetics
Time-lagged autoencoders: Deep learning of slow collective variables for molecular kinetics
C. Wehmeyer
Frank Noé
AI4CE
BDL
111
357
0
30 Oct 2017
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