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VAMPnets: Deep learning of molecular kinetics
v1v2 (latest)

VAMPnets: Deep learning of molecular kinetics

16 October 2017
Andreas Mardt
Luca Pasquali
Hao Wu
Frank Noé
ArXiv (abs)PDFHTML

Papers citing "VAMPnets: Deep learning of molecular kinetics"

50 / 134 papers shown
Title
Prediction of good reaction coordinates and future evolution of MD trajectories using Regularized Sparse Autoencoders: A novel deep learning approach
Abhijit Gupta
67
0
0
22 Aug 2022
Thermodynamics-inspired Explanations of Artificial Intelligence
Thermodynamics-inspired Explanations of Artificial Intelligence
S. Mehdi
P. Tiwary
AI4CE
65
18
0
27 Jun 2022
SAIBench: Benchmarking AI for Science
SAIBench: Benchmarking AI for Science
Yatao Li
Jianfeng Zhan
51
7
0
11 Jun 2022
Learning Dynamical Systems via Koopman Operator Regression in
  Reproducing Kernel Hilbert Spaces
Learning Dynamical Systems via Koopman Operator Regression in Reproducing Kernel Hilbert Spaces
Vladimir Kostic
P. Novelli
Andreas Maurer
C. Ciliberto
Lorenzo Rosasco
Massimiliano Pontil
78
62
0
27 May 2022
Learning Geometrically Disentangled Representations of Protein Folding
  Simulations
Learning Geometrically Disentangled Representations of Protein Folding Simulations
N. Joseph Tatro
Payel Das
Pin-Yu Chen
Vijil Chenthamarakshan
Rongjie Lai
AI4CE
57
0
0
20 May 2022
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
Characterizing metastable states with the help of machine learning
Characterizing metastable states with the help of machine learning
P. Novelli
L. Bonati
Massimiliano Pontil
Michele Parrinello
53
23
0
15 Apr 2022
Prediction of transport property via machine learning molecular
  movements
Prediction of transport property via machine learning molecular movements
Ikki Yasuda
Yusei Kobayashi
Katsuhiro Endo
Yoshihiro Hayakawa
Kazuhiko Fujiwara
K. Yajima
N. Arai
K. Yasuoka
20
1
0
07 Mar 2022
Learning stochastic dynamics and predicting emergent behavior using
  transformers
Learning stochastic dynamics and predicting emergent behavior using transformers
Corneel Casert
Isaac Tamblyn
S. Whitelam
AI4CE
53
9
0
17 Feb 2022
MD-GAN with multi-particle input: the machine learning of long-time
  molecular behavior from short-time MD data
MD-GAN with multi-particle input: the machine learning of long-time molecular behavior from short-time MD data
Ryo Kawada
Katsuhiro Endo
Daisuke Yuhara
K. Yasuoka
AI4CE
51
2
0
02 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
GraphVAMPNet, using graph neural networks and variational approach to
  markov processes for dynamical modeling of biomolecules
GraphVAMPNet, using graph neural networks and variational approach to markov processes for dynamical modeling of biomolecules
Mahdi Ghorbani
Samarjeet Prasad
Jeffery B. Klauda
B. Brooks
GNN
51
32
0
12 Jan 2022
Rigorous data-driven computation of spectral properties of Koopman
  operators for dynamical systems
Rigorous data-driven computation of spectral properties of Koopman operators for dynamical systems
Matthew J. Colbrook
Alex Townsend
95
72
0
29 Nov 2021
Learning Low-Dimensional Quadratic-Embeddings of High-Fidelity Nonlinear
  Dynamics using Deep Learning
Learning Low-Dimensional Quadratic-Embeddings of High-Fidelity Nonlinear Dynamics using Deep Learning
P. Goyal
P. Benner
AI4CE
51
5
0
25 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
Learning Stable Koopman Embeddings
Learning Stable Koopman Embeddings
Fletcher Fan
Yeman Fan
D. Rye
Guodong Shi
I. Manchester
92
34
0
13 Oct 2021
Enhancing Computational Fluid Dynamics with Machine Learning
Enhancing Computational Fluid Dynamics with Machine Learning
Ricardo Vinuesa
Steven L. Brunton
AI4CE
186
385
0
05 Oct 2021
Applying Machine Learning to Study Fluid Mechanics
Applying Machine Learning to Study Fluid Mechanics
Steven L. Brunton
PINNAI4CE
63
100
0
05 Oct 2021
Self-Supervised Decomposition, Disentanglement and Prediction of Video
  Sequences while Interpreting Dynamics: A Koopman Perspective
Self-Supervised Decomposition, Disentanglement and Prediction of Video Sequences while Interpreting Dynamics: A Koopman Perspective
Armand Comas Massague
S. Ghimire
Haolin Li
Octavia Camps
Mario Sznaier
112
2
0
01 Oct 2021
Extended dynamic mode decomposition with dictionary learning using
  neural ordinary differential equations
Extended dynamic mode decomposition with dictionary learning using neural ordinary differential equations
H. Terao
Sho Shirasaka
Hideyuki Suzuki
58
6
0
01 Oct 2021
Deep Learning Enhanced Dynamic Mode Decomposition
Deep Learning Enhanced Dynamic Mode Decomposition
D. J. Alford-Lago
C. Curtis
Alexander T. Ihler
Opal Issan
75
36
0
10 Aug 2021
Ten Quick Tips for Deep Learning in Biology
Ten Quick Tips for Deep Learning in Biology
Benjamin D. Lee
A. Gitter
Casey S. Greene
S. Raschka
F. Maguire
...
Alexandr A Kalinin
T. Triche
Benjamin J. Lengerich
Timothy J. Triche Jr
S. Boca
OOD
104
27
0
29 May 2021
Operator Autoencoders: Learning Physical Operations on Encoded Molecular
  Graphs
Operator Autoencoders: Learning Physical Operations on Encoded Molecular Graphs
Willis Hoke
D. Shea
S. Casey
AI4CE
57
0
0
26 May 2021
Chasing Collective Variables using Autoencoders and biased trajectories
Chasing Collective Variables using Autoencoders and biased trajectories
Zineb Belkacemi
P. Gkeka
T. Lelièvre
G. Stoltz
AI4CE
58
63
0
22 Apr 2021
Coupling streaming AI and HPC ensembles to achieve 100-1000x faster
  biomolecular simulations
Coupling streaming AI and HPC ensembles to achieve 100-1000x faster biomolecular simulations
Alexander Brace
I. Yakushin
Heng Ma
Anda Trifan
T. Munson
Ian Foster
A. Ramanathan
Hyungro Lee
Matteo Turilli
S. Jha
AI4CE
77
20
0
10 Apr 2021
Deep Learning of Conjugate Mappings
Deep Learning of Conjugate Mappings
J. Bramburger
S. Patterson
J. Nathan Kutz
75
15
0
01 Apr 2021
Modern Koopman Theory for Dynamical Systems
Modern Koopman Theory for Dynamical Systems
Steven L. Brunton
M. Budišić
E. Kaiser
J. Nathan Kutz
AI4CE
156
423
0
24 Feb 2021
CKNet: A Convolutional Neural Network Based on Koopman Operator for
  Modeling Latent Dynamics from Pixels
CKNet: A Convolutional Neural Network Based on Koopman Operator for Modeling Latent Dynamics from Pixels
Yongqian Xiao
Xin Xu
Yifei Shi
60
9
0
19 Feb 2021
Accelerated Simulations of Molecular Systems through Learning of their
  Effective Dynamics
Accelerated Simulations of Molecular Systems through Learning of their Effective Dynamics
Pantelis R. Vlachas
Julija Zavadlav
M. Praprotnik
Petros Koumoutsakos
AI4CE
56
3
0
17 Feb 2021
An Operator Theoretic Approach for Analyzing Sequence Neural Networks
An Operator Theoretic Approach for Analyzing Sequence Neural Networks
Ilana D Naiman
Omri Azencot
108
11
0
15 Feb 2021
Accuracy and Architecture Studies of Residual Neural Network solving
  Ordinary Differential Equations
Accuracy and Architecture Studies of Residual Neural Network solving Ordinary Differential Equations
Changxin Qiu
Aaron Bendickson
Joshua Kalyanapu
Jue Yan
37
1
0
10 Jan 2021
DeepGreen: Deep Learning of Green's Functions for Nonlinear Boundary
  Value Problems
DeepGreen: Deep Learning of Green's Functions for Nonlinear Boundary Value Problems
Craig Gin
D. Shea
Steven L. Brunton
J. Nathan Kutz
92
90
0
31 Dec 2020
Artificial intelligence techniques for integrative structural biology of
  intrinsically disordered proteins
Artificial intelligence techniques for integrative structural biology of intrinsically disordered proteins
A. Ramanathan
Henglong Ma
Akash Parvatikar
C. Chennubhotla
AI4CE
55
40
0
01 Dec 2020
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
Spacetime Autoencoders Using Local Causal States
Spacetime Autoencoders Using Local Causal States
Adam T. Rupe
James P. Crutchfield
CML
140
2
0
12 Oct 2020
Automatic Differentiation to Simultaneously Identify Nonlinear Dynamics
  and Extract Noise Probability Distributions from Data
Automatic Differentiation to Simultaneously Identify Nonlinear Dynamics and Extract Noise Probability Distributions from Data
Kadierdan Kaheman
Steven L. Brunton
J. Nathan Kutz
85
84
0
12 Sep 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
Molecular Latent Space Simulators
Molecular Latent Space Simulators
Hythem Sidky
Wei Chen
Andrew L. Ferguson
AI4CE
77
34
0
01 Jul 2020
Difference-Based Deep Learning Framework for Stress Predictions in
  Heterogeneous Media
Difference-Based Deep Learning Framework for Stress Predictions in Heterogeneous Media
Haotian Feng
P. Prabhakar
59
34
0
01 Jul 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
A Perspective on Deep Learning for Molecular Modeling and Simulations
A Perspective on Deep Learning for Molecular Modeling and Simulations
Jun Zhang
Yao-Kun Lei
Zhen Zhang
Junhan Chang
Maodong Li
Xu Han
Lijiang Yang
Yue Yang
Y. Gao
AI4CE
116
8
0
25 Apr 2020
Multiresolution Convolutional Autoencoders
Multiresolution Convolutional Autoencoders
Yuying Liu
Colin Ponce
Steven L. Brunton
J. Nathan Kutz
SyDa
52
31
0
10 Apr 2020
SINDy-PI: A Robust Algorithm for Parallel Implicit Sparse Identification
  of Nonlinear Dynamics
SINDy-PI: A Robust Algorithm for Parallel Implicit Sparse Identification of Nonlinear Dynamics
Kadierdan Kaheman
J. Nathan Kutz
Steven L. Brunton
76
275
0
05 Apr 2020
Autonomous discovery in the chemical sciences part II: Outlook
Autonomous discovery in the chemical sciences part II: Outlook
Connor W. Coley
Natalie S. Eyke
K. Jensen
91
175
0
30 Mar 2020
Autonomous discovery in the chemical sciences part I: Progress
Autonomous discovery in the chemical sciences part I: Progress
Connor W. Coley
Natalie S. Eyke
K. Jensen
71
218
0
30 Mar 2020
Integrating Scientific Knowledge with Machine Learning for Engineering
  and Environmental Systems
Integrating Scientific Knowledge with Machine Learning for Engineering and Environmental Systems
J. Willard
X. Jia
Shaoming Xu
M. Steinbach
Vipin Kumar
AI4CE
158
415
0
10 Mar 2020
Methods to Recover Unknown Processes in Partial Differential Equations
  Using Data
Methods to Recover Unknown Processes in Partial Differential Equations Using Data
Zhen Chen
Kailiang Wu
D. Xiu
55
3
0
05 Mar 2020
Forecasting Sequential Data using Consistent Koopman Autoencoders
Forecasting Sequential Data using Consistent Koopman Autoencoders
Omri Azencot
N. Benjamin Erichson
Vanessa Lin
Michael W. Mahoney
AI4TSAI4CE
206
152
0
04 Mar 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
Deep reconstruction of strange attractors from time series
Deep reconstruction of strange attractors from time series
W. Gilpin
AI4TS
43
3
0
14 Feb 2020
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