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Deep Generative Markov State Models
v1v2 (latest)

Deep Generative Markov State Models

19 May 2018
Hao Wu
Andreas Mardt
Luca Pasquali
Frank Noe
    AI4CE
ArXiv (abs)PDFHTML

Papers citing "Deep Generative Markov State Models"

28 / 28 papers shown
Title
Predicting the Energy Landscape of Stochastic Dynamical System via Physics-informed Self-supervised Learning
Predicting the Energy Landscape of Stochastic Dynamical System via Physics-informed Self-supervised Learning
Ruikun Li
Huandong Wang
Qingmin Liao
Yong Li
57
2
0
24 Feb 2025
Designing Long-term Group Fair Policies in Dynamical Systems
Designing Long-term Group Fair Policies in Dynamical Systems
Miriam Rateike
Isabel Valera
Patrick Forré
93
5
0
21 Nov 2023
Latent Representation and Simulation of Markov Processes via Time-Lagged
  Information Bottleneck
Latent Representation and Simulation of Markov Processes via Time-Lagged Information Bottleneck
Marco Federici
Patrick Forré
Ryota Tomioka
Bastiaan S. Veeling
53
6
0
13 Sep 2023
Implicit Transfer Operator Learning: Multiple Time-Resolution Surrogates
  for Molecular Dynamics
Implicit Transfer Operator Learning: Multiple Time-Resolution Surrogates for Molecular Dynamics
Mathias Jacob Schreiner
Ole Winther
Simon Olsson
OODAI4CE
129
13
0
29 May 2023
Timewarp: Transferable Acceleration of Molecular Dynamics by Learning
  Time-Coarsened Dynamics
Timewarp: Transferable Acceleration of Molecular Dynamics by Learning Time-Coarsened Dynamics
Leon Klein
Andrew Y. K. Foong
T. E. Fjelde
Bruno Mlodozeniec
Marc Brockschmidt
Sebastian Nowozin
Frank Noé
Ryota Tomioka
AI4CE
144
47
0
02 Feb 2023
Simulate Time-integrated Coarse-grained Molecular Dynamics with
  Multi-Scale Graph Networks
Simulate Time-integrated Coarse-grained Molecular Dynamics with Multi-Scale Graph Networks
Xiang Fu
T. Xie
Nathan J. Rebello
B. Olsen
Tommi Jaakkola
AI4CE
75
15
0
21 Apr 2022
Dimensionally Consistent Learning with Buckingham Pi
Dimensionally Consistent Learning with Buckingham Pi
Joseph Bakarji
Jared L. Callaham
Steven L. Brunton
N. Kutz
64
41
0
09 Feb 2022
Discovering Governing Equations from Partial Measurements with Deep
  Delay Autoencoders
Discovering Governing Equations from Partial Measurements with Deep Delay Autoencoders
Joseph Bakarji
Kathleen P. Champion
J. Nathan Kutz
Steven L. Brunton
111
86
0
13 Jan 2022
On the Stochastic Stability of Deep Markov Models
On the Stochastic Stability of Deep Markov Models
Ján Drgoňa
Sayak Mukherjee
Jiaxin Zhang
Frank Liu
M. Halappanavar
BDL
58
7
0
08 Nov 2021
Constructing Neural Network-Based Models for Simulating Dynamical
  Systems
Constructing Neural Network-Based Models for Simulating Dynamical Systems
Christian Møldrup Legaard
Thomas Schranz
G. Schweiger
Ján Drgovna
Basak Falay
C. Gomes
Alexandros Iosifidis
M. Abkar
P. Larsen
PINNAI4CE
63
98
0
02 Nov 2021
Deeptime: a Python library for machine learning dynamical models from
  time series data
Deeptime: a Python library for machine learning dynamical models from time series data
Moritz Hoffmann
Martin K. Scherer
Tim Hempel
Andreas Mardt
Brian M. de Silva
...
Stefan Klus
Hao Wu
N. Kutz
Steven L. Brunton
Frank Noé
AI4CE
101
107
0
28 Oct 2021
Variational Inference for Continuous-Time Switching Dynamical Systems
Variational Inference for Continuous-Time Switching Dynamical Systems
Lukas Kohs
Bastian Alt
Heinz Koeppl
91
8
0
29 Sep 2021
A Physics Informed Neural Network Approach to Solution and
  Identification of Biharmonic Equations of Elasticity
A Physics Informed Neural Network Approach to Solution and Identification of Biharmonic Equations of Elasticity
M. Vahab
E. Haghighat
M. Khaleghi
N. Khalili
PINN
120
45
0
16 Aug 2021
Physics-aware, probabilistic model order reduction with guaranteed
  stability
Physics-aware, probabilistic model order reduction with guaranteed stability
Sebastian Kaltenbach
P. Koutsourelakis
DiffMAI4CE
88
15
0
14 Jan 2021
Machine Learning Force Fields
Machine Learning Force Fields
Oliver T. Unke
Stefan Chmiela
H. E. Sauceda
M. Gastegger
I. Poltavsky
Kristof T. Schütt
A. Tkatchenko
K. Müller
AI4CE
141
940
0
14 Oct 2020
Machine Learning in Nano-Scale Biomedical Engineering
Machine Learning in Nano-Scale Biomedical Engineering
Alexandros-Apostolos A. Boulogeorgos
Stylianos E. Trevlakis
Sotiris A. Tegos
V. Papanikolaou
G. Karagiannidis
AI4CE
41
30
0
05 Aug 2020
Markov-Lipschitz Deep Learning
Markov-Lipschitz Deep Learning
Stan Z. Li
Zelin Zhang
Lirong Wu
77
16
0
15 Jun 2020
A Combined Data-driven and Physics-driven Method for Steady Heat
  Conduction Prediction using Deep Convolutional Neural Networks
A Combined Data-driven and Physics-driven Method for Steady Heat Conduction Prediction using Deep Convolutional Neural Networks
Hao Ma
Xiangyu Y. Hu
Yuxuan Zhang
Nils Thuerey
O. Haidn
AI4CE
48
12
0
16 May 2020
Ensemble Learning of Coarse-Grained Molecular Dynamics Force Fields with
  a Kernel Approach
Ensemble Learning of Coarse-Grained Molecular Dynamics Force Fields with a Kernel Approach
Jiang Wang
Stefan Chmiela
K. Müller
Frank Noè
C. Clementi
138
46
0
04 May 2020
Differentiable Molecular Simulations for Control and Learning
Differentiable Molecular Simulations for Control and Learning
Wujie Wang
Simon Axelrod
Rafael Gómez-Bombarelli
AI4CE
196
49
0
27 Feb 2020
Incorporating physical constraints in a deep probabilistic machine
  learning framework for coarse-graining dynamical systems
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
Attention network forecasts time-to-failure in laboratory shear
  experiments
Attention network forecasts time-to-failure in laboratory shear experiments
H. Jasperson
D. C. Bolton
P. Johnson
R. Guyer
C. Marone
Maarten V. de Hoop
39
18
0
12 Dec 2019
Machine learning for molecular simulation
Machine learning for molecular simulation
Frank Noé
A. Tkatchenko
K. Müller
C. Clementi
AI4CE
90
668
0
07 Nov 2019
A General Framework for Uncertainty Estimation in Deep Learning
A General Framework for Uncertainty Estimation in Deep Learning
Antonio Loquercio
Mattia Segu
Davide Scaramuzza
UQCVBDLOOD
103
293
0
16 Jul 2019
Machine Learning for Fluid Mechanics
Machine Learning for Fluid Mechanics
Steven Brunton
B. R. Noack
Petros Koumoutsakos
AI4CEPINN
103
2,146
0
27 May 2019
Graph Dynamical Networks for Unsupervised Learning of Atomic Scale
  Dynamics in Materials
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
Machine Learning for Molecular Dynamics on Long Timescales
Machine Learning for Molecular Dynamics on Long Timescales
Frank Noé
AI4CE
77
32
0
18 Dec 2018
Machine Learning of coarse-grained Molecular Dynamics Force Fields
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
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