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Deep Generative Markov State Models

19 May 2018

Frank Noe

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 Ruikun Li Huandong Wang Qingmin Liao Yong Li 57 2 0 24 Feb 2025
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 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 Mathias Jacob Schreiner Ole Winther Simon Olsson OOD AI4CE 129 13 0 29 May 2023
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 Xiang Fu T. Xie Nathan J. Rebello B. Olsen Tommi Jaakkola AI4CE 75 15 0 21 Apr 2022
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 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 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 Christian Møldrup Legaard Thomas Schranz G. Schweiger Ján Drgovna Basak Falay C. Gomes Alexandros Iosifidis M. Abkar P. Larsen PINN AI4CE 63 98 0 02 Nov 2021
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 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 M. Vahab E. Haghighat M. Khaleghi N. Khalili PINN 120 45 0 16 Aug 2021
Physics-aware, probabilistic model order reduction with guaranteed stability Sebastian Kaltenbach P. Koutsourelakis DiffM AI4CE 88 15 0 14 Jan 2021
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 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 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 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 Jiang Wang Stefan Chmiela K. Müller Frank Noè C. Clementi 138 46 0 04 May 2020
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 Sebastian Kaltenbach P. Koutsourelakis AI4CE 205 35 0 30 Dec 2019
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 Frank Noé A. Tkatchenko K. Müller C. Clementi AI4CE 90 668 0 07 Nov 2019
A General Framework for Uncertainty Estimation in Deep Learning Antonio Loquercio Mattia Segu Davide Scaramuzza UQCV BDL OOD 101 293 0 16 Jul 2019
Machine Learning for Fluid Mechanics Steven Brunton B. R. Noack Petros Koumoutsakos AI4CE PINN 103 2,146 0 27 May 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
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 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