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VAMPnets: Deep learning of molecular kinetics

16 October 2017

Frank Noé

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 48 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 69 111 0 18 Feb 2019
Nonlinear Discovery of Slow Molecular Modes using State-Free Reversible VAMPnets Wei Chen Hythem Sidky Andrew L. Ferguson 54 100 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 117 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 71 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 65 374 0 12 Oct 2017
Variational approach for learning Markov processes from time series data Hao Wu Frank Noé BDL AI4TS 86 266 0 14 Jul 2017