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VAMPnets: Deep learning of molecular kinetics

16 October 2017

Frank Noé

Papers citing "VAMPnets: Deep learning of molecular kinetics"

50 / 134 papers shown

Title
Learning collective variables that preserve transition rates Shashank Sule Arnav Mehta Maria Cameron 78 0 0 02 Jun 2025
Dynamic Manifold Evolution Theory: Modeling and Stability Analysis of Latent Representations in Large Language Models Yukun Zhang Qi Dong AI4CE 26 0 0 24 May 2025
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
Al-Khwarizmi: Discovering Physical Laws with Foundation Models Christopher E. Mower Haitham Bou-Ammar AI4CE 211 2 0 03 Feb 2025
Machine Learning of Slow Collective Variables and Enhanced Sampling via Spatial Techniques Tuğçe Gökdemir Jakub Rydzewski 112 2 0 31 Dec 2024
Pushing the Limits of All-Atom Geometric Graph Neural Networks: Pre-Training, Scaling and Zero-Shot Transfer Zihan Pengmei Zhengyuan Shen Zichen Wang Marcus Collins Huzefa Rangwala AI4CE 65 2 0 29 Oct 2024
Laplace Transform Based Low-Complexity Learning of Continuous Markov Semigroups Vladimir Kostic Karim Lounici Helene Halconruy Timothée Devergne P. Novelli Massimiliano Pontil 73 0 0 18 Oct 2024
Balanced Neural ODEs: nonlinear model order reduction and Koopman operator approximations Julius Aka Johannes Brunnemann Jörg Eiden Arne Speerforck Lars Mikelsons 100 0 0 14 Oct 2024
MetaGFN: Exploring Distant Modes with Adapted Metadynamics for Continuous GFlowNets Dominic Phillips F. Cipcigan 107 4 0 28 Aug 2024
4D Diffusion for Dynamic Protein Structure Prediction with Reference Guided Motion Alignment Kaihui Cheng Ce Liu Qingkun Su Jun Wang Liwei Zhang Yining Tang Yao Yao Siyu Zhu Yuan Qi DiffM 58 1 0 22 Aug 2024
Parameter inference from a non-stationary unknown process Kieran S. Owens Ben D. Fulcher AI4TS 66 1 0 12 Jul 2024
Feasibility Study on Active Learning of Smart Surrogates for Scientific Simulations Pradeep Bajracharya J. Q. Toledo-Marín Geoffrey C. Fox S. Jha Linwei Wang AI4CE 97 1 0 10 Jul 2024
From Biased to Unbiased Dynamics: An Infinitesimal Generator Approach Timothée Devergne Vladimir Kostic Michele Parrinello Massimiliano Pontil 72 3 0 13 Jun 2024
Foundation Inference Models for Markov Jump Processes David Berghaus K. Cvejoski Patrick Seifner C. Ojeda Ramses J. Sanchez 101 1 0 10 Jun 2024
Learning the Infinitesimal Generator of Stochastic Diffusion Processes Vladimir Kostic Karim Lounici Helene Halconruy Timothée Devergne Massimiliano Pontil DiffM 62 4 0 21 May 2024
Dynamical systems and complex networks: A Koopman operator perspective Stefan Klus Natavsa Djurdjevac Conrad 51 3 0 14 May 2024
Kinematics Modeling of Peroxy Free Radicals: A Deep Reinforcement Learning Approach Subhadarsi Nayak H. Shalu J. Stember 20 0 0 12 Apr 2024
Koopman-Assisted Reinforcement Learning Preston Rozwood Edward Mehrez Ludger Paehler Wen Sun Steven L. Brunton 109 10 0 04 Mar 2024
Phase autoencoder for limit-cycle oscillators K. Yawata Kai Fukami Kunihiko Taira Hiroya Nakao 126 9 0 28 Feb 2024
Large Scale Training of Graph Neural Networks for Optimal Markov-Chain Partitioning Using the Kemeny Constant S. Martino João Morado Chenghao Li Zhenghao Lu E. Rosta GNN 18 0 0 22 Dec 2023
Data-driven path collective variables Arthur France-Lanord Hadrien Vroylandt M. Salanne B. Rotenberg A. M. Saitta F. Pietrucci 68 13 0 21 Dec 2023
Hierarchical deep learning-based adaptive time-stepping scheme for multiscale simulations Asif Hamid Danish Rafiq S. A. Nahvi M. A. Bazaz AI4CE 85 2 0 10 Nov 2023
Unsupervised Learning of Molecular Embeddings for Enhanced Clustering and Emergent Properties for Chemical Compounds Jaiveer Gill Ratul Chakraborty Reetham Gubba Amy Liu Shrey Jain Chirag Iyer Obaid Khwaja Saurav Kumar 125 0 0 25 Oct 2023
Koopman Invertible Autoencoder: Leveraging Forward and Backward Dynamics for Temporal Modeling Kshitij Tayal Arvind Renganathan Rahul Ghosh X. Jia Vipin Kumar SyDa AI4CE 89 5 0 19 Sep 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
Early warning indicators via latent stochastic dynamical systems Lingyu Feng Ting Gao Wang Xiao Jinqiao Duan 61 3 0 07 Sep 2023
Deep Learning for Structure-Preserving Universal Stable Koopman-Inspired Embeddings for Nonlinear Canonical Hamiltonian Dynamics P. Goyal Süleyman Yıldız P. Benner 87 3 0 26 Aug 2023
Learning invariant representations of time-homogeneous stochastic dynamical systems Vladimir Kostic P. Novelli Riccardo Grazzi Karim Lounici Massimiliano Pontil 70 8 0 19 Jul 2023
Understanding recent deep-learning techniques for identifying collective variables of molecular dynamics Wei Zhang Christof Schütte 33 5 0 01 Jul 2023
Elucidating Interfacial Dynamics of Ti-Al Systems Using Molecular Dynamics Simulation and Markov State Modeling Tianjiao Li Chenxi Tian A. Moridi Jingjie Yeo AI4CE 22 3 0 26 Jun 2023
PyKoopman: A Python Package for Data-Driven Approximation of the Koopman Operator Shaowu Pan E. Kaiser Brian M. de Silva J. Nathan Kutz Steven L. Brunton 118 8 0 22 Jun 2023
Enhanced Sampling with Machine Learning: A Review S. Mehdi Zachary Smith Lukas Herron Ziyue Zou P. Tiwary AI4CE 52 8 0 15 Jun 2023
Improving Estimation of the Koopman Operator with Kolmogorov-Smirnov Indicator Functions Van A. Ngo Yen Ting Lin D. Perez 13 0 0 09 Jun 2023
Neural Markov Jump Processes Patrick Seifner Ramses J. Sanchez BDL 81 8 0 31 May 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
Koopman Kernel Regression Petar Bevanda Maximilian Beier Armin Lederer Stefan Sosnowski Eyke Hüllermeier Sandra Hirche AI4TS 84 16 0 25 May 2023
Machine Learning for Partial Differential Equations Steven L. Brunton J. Nathan Kutz AI4CE 101 21 0 30 Mar 2023
Inexact iterative numerical linear algebra for neural network-based spectral estimation and rare-event prediction J. Strahan Spencer C. Guo Chatipat Lorpaiboon Aaron R Dinner Jonathan Weare 133 9 0 22 Mar 2023
Internal-Coordinate Density Modelling of Protein Structure: Covariance Matters Marloes Arts J. Frellsen Wouter Boomsma 78 1 0 27 Feb 2023
Geometric Clifford Algebra Networks David Ruhe Jayesh K. Gupta Steven De Keninck Max Welling Johannes Brandstetter AI4CE 139 38 0 13 Feb 2023
Sharp Spectral Rates for Koopman Operator Learning Vladimir Kostic Karim Lounici P. Novelli Massimiliano Pontil 150 24 0 03 Feb 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
Fast conformational clustering of extensive molecular dynamics simulation data Simon Hunkler K. Diederichs O. Kukharenko Christine Peter 63 9 0 11 Jan 2023
Neuro-DynaStress: Predicting Dynamic Stress Distributions in Structural Components H. Bolandi Gautam Sreekumar Xuyang Li N. Lajnef Vishnu Boddeti AI4CE 15 2 0 19 Dec 2022
SchNetPack 2.0: A neural network toolbox for atomistic machine learning Kristof T. Schütt Stefaan S. P. Hessmann Niklas W. A. Gebauer Jonas Lederer M. Gastegger 78 65 0 11 Dec 2022
Physics Informed Neural Network for Dynamic Stress Prediction H. Bolandi Gautam Sreekumar Xuyang Li N. Lajnef Vishnu Boddeti AI4CE 56 23 0 28 Nov 2022
DLKoopman: A deep learning software package for Koopman theory Sourya Dey Eric K. Davis AI4CE 74 4 0 15 Nov 2022
Generalized Quadratic Embeddings for Nonlinear Dynamics using Deep Learning P. Goyal P. Benner 74 12 0 01 Nov 2022
Rethinking skip connection model as a learnable Markov chain Dengsheng Chen Jie Hu Jingyao Wang Xiaoming Wei Enhua Wu BDL 115 1 0 30 Sep 2022
Algorithmic Differentiation for Automated Modeling of Machine Learned Force Fields Niklas Schmitz Klaus-Robert Muller Stefan Chmiela AI4CE 75 11 0 25 Aug 2022