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1710.06012
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VAMPnets: Deep learning of molecular kinetics
16 October 2017
Andreas Mardt
Luca Pasquali
Hao Wu
Frank Noé
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Papers citing
"VAMPnets: Deep learning of molecular kinetics"
34 / 134 papers shown
Title
Incorporating physical constraints in a deep probabilistic machine learning framework for coarse-graining dynamical systems
Sebastian Kaltenbach
P. Koutsourelakis
AI4CE
205
35
0
30 Dec 2019
Interpretable Embeddings From Molecular Simulations Using Gaussian Mixture Variational Autoencoders
Yasemin Bozkurt Varolgunes
T. Bereau
J. F. Rudzinski
DRL
58
44
0
22 Dec 2019
Machine learning for protein folding and dynamics
Frank Noé
Gianni De Fabritiis
C. Clementi
AI4CE
121
138
0
22 Nov 2019
Machine learning for molecular simulation
Frank Noé
A. Tkatchenko
K. Müller
C. Clementi
AI4CE
90
668
0
07 Nov 2019
Deep Learning Models for Global Coordinate Transformations that Linearize PDEs
Craig Gin
Bethany Lusch
Steven L. Brunton
J. Nathan Kutz
83
41
0
07 Nov 2019
Neural Canonical Transformation with Symplectic Flows
Shuo-Hui Li
Chen Dong
Linfeng Zhang
Lei Wang
DRL
119
28
0
30 Sep 2019
Learning Everywhere: A Taxonomy for the Integration of Machine Learning and Simulations
Geoffrey C. Fox
S. Jha
AI4CE
72
13
0
29 Sep 2019
Data-driven approximation of the Koopman generator: Model reduction, system identification, and control
Stefan Klus
Feliks Nuske
Sebastian Peitz
Jan-Hendrik Niemann
C. Clementi
Christof Schütte
118
230
0
23 Sep 2019
DeepDriveMD: Deep-Learning Driven Adaptive Molecular Simulations for Protein Folding
Hyungro Lee
Heng Ma
Matteo Turilli
D. Bhowmik
S. Jha
A. Ramanathan
AI4CE
54
71
0
17 Sep 2019
Tensor-based computation of metastable and coherent sets
Feliks Nuske
Patrick Gelß
Stefan Klus
C. Clementi
32
13
0
12 Aug 2019
A unified sparse optimization framework to learn parsimonious physics-informed models from data
Kathleen P. Champion
P. Zheng
Aleksandr Aravkin
Steven L. Brunton
J. Nathan Kutz
AI4CE
74
119
0
25 Jun 2019
High-resolution Markov state models for the dynamics of Trp-cage miniprotein constructed over slow folding modes identified by state-free reversible VAMPnets
Hythem Sidky
Wei Chen
Andrew L. Ferguson
74
55
0
12 Jun 2019
Capabilities and Limitations of Time-lagged Autoencoders for Slow Mode Discovery in Dynamical Systems
Wei Chen
Hythem Sidky
Andrew L. Ferguson
76
36
0
02 Jun 2019
Machine Learning for Fluid Mechanics
Steven Brunton
B. R. Noack
Petros Koumoutsakos
AI4CE
PINN
103
2,146
0
27 May 2019
Structure-preserving Method for Reconstructing Unknown Hamiltonian Systems from Trajectory Data
Kailiang Wu
Tong Qin
D. Xiu
78
31
0
24 May 2019
Approximation spaces of deep neural networks
Rémi Gribonval
Gitta Kutyniok
M. Nielsen
Felix Voigtländer
111
126
0
03 May 2019
Dimensionality Reduction of Complex Metastable Systems via Kernel Embeddings of Transition Manifolds
A. Bittracher
Stefan Klus
B. Hamzi
P. Koltai
Christof Schütte
78
22
0
18 Apr 2019
Kernel methods for detecting coherent structures in dynamical data
Stefan Klus
B. Husic
Mattes Mollenhauer
Frank Noé
54
29
0
16 Apr 2019
Time Series Source Separation using Dynamic Mode Decomposition
Arvind Prasadan
R. Nadakuditi
AI4TS
88
6
0
04 Mar 2019
Graph Dynamical Networks for Unsupervised Learning of Atomic Scale Dynamics in Materials
T. Xie
A. France-Lanord
Yanming Wang
Y. Shao-horn
Jeffrey C. Grossman
AI4CE
75
111
0
18 Feb 2019
Nonlinear Discovery of Slow Molecular Modes using State-Free Reversible VAMPnets
Wei Chen
Hythem Sidky
Andrew L. Ferguson
59
100
0
09 Feb 2019
Machine Learning for Molecular Dynamics on Long Timescales
Frank Noé
AI4CE
77
32
0
18 Dec 2018
Coarse-Graining Auto-Encoders for Molecular Dynamics
Wujie Wang
Rafael Gómez-Bombarelli
AI4CE
70
167
0
06 Dec 2018
Machine Learning of coarse-grained Molecular Dynamics Force Fields
Jiang Wang
Simon Olsson
C. Wehmeyer
Adria Pérez
Nicholas E. Charron
Gianni De Fabritiis
Frank Noe
C. Clementi
AI4CE
83
407
0
04 Dec 2018
Variational Selection of Features for Molecular Kinetics
Martin K. Scherer
B. Husic
Moritz Hoffmann
Fabian Paul
Hao Wu
Frank Noé
120
50
0
28 Nov 2018
Data Driven Governing Equations Approximation Using Deep Neural Networks
Tong Qin
Kailiang Wu
D. Xiu
PINN
98
275
0
13 Nov 2018
A kernel-based approach to molecular conformation analysis
Stefan Klus
A. Bittracher
Ingmar Schuster
Christof Schütte
57
26
0
28 Sep 2018
Stress Field Prediction in Cantilevered Structures Using Convolutional Neural Networks
Zhenguo Nie
Haoliang Jiang
Levent Burak Kara
53
144
0
27 Aug 2018
Deep Generative Markov State Models
Hao Wu
Andreas Mardt
Luca Pasquali
Frank Noe
AI4CE
78
60
0
19 May 2018
Deep learning for universal linear embeddings of nonlinear dynamics
Bethany Lusch
J. Nathan Kutz
Steven L. Brunton
87
1,268
0
27 Dec 2017
Variational Encoding of Complex Dynamics
Carlos X. Hernández
H. Wayment-Steele
Mohammad M. Sultan
B. Husic
Vijay S. Pande
AI4CE
91
140
0
23 Nov 2017
Time-lagged autoencoders: Deep learning of slow collective variables for molecular kinetics
C. Wehmeyer
Frank Noé
AI4CE
BDL
179
362
0
30 Oct 2017
Learning Koopman Invariant Subspaces for Dynamic Mode Decomposition
Naoya Takeishi
Yoshinobu Kawahara
Takehisa Yairi
67
374
0
12 Oct 2017
Variational approach for learning Markov processes from time series data
Hao Wu
Frank Noé
BDL
AI4TS
89
266
0
14 Jul 2017
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