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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
Prediction of good reaction coordinates and future evolution of MD trajectories using Regularized Sparse Autoencoders: A novel deep learning approach Abhijit Gupta 59 0 0 22 Aug 2022
Thermodynamics-inspired Explanations of Artificial Intelligence S. Mehdi P. Tiwary AI4CE 65 18 0 27 Jun 2022
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 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 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 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 P. Novelli L. Bonati Massimiliano Pontil Michele Parrinello 50 23 0 15 Apr 2022
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 17 1 0 07 Mar 2022
Learning stochastic dynamics and predicting emergent behavior using transformers Corneel Casert Isaac Tamblyn S. Whitelam AI4CE 50 9 0 17 Feb 2022
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 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 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 Matthew J. Colbrook Alex Townsend 95 72 0 29 Nov 2021
Learning Low-Dimensional Quadratic-Embeddings of High-Fidelity Nonlinear Dynamics using Deep Learning P. Goyal P. Benner AI4CE 47 5 0 25 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
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 Ricardo Vinuesa Steven L. Brunton AI4CE 186 385 0 05 Oct 2021
Applying Machine Learning to Study Fluid Mechanics Steven L. Brunton PINN AI4CE 63 100 0 05 Oct 2021
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 H. Terao Sho Shirasaka Hideyuki Suzuki 58 6 0 01 Oct 2021
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 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 Willis Hoke D. Shea S. Casey AI4CE 57 0 0 26 May 2021
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 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 J. Bramburger S. Patterson J. Nathan Kutz 75 15 0 01 Apr 2021
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 Yongqian Xiao Xin Xu Yifei Shi 60 9 0 19 Feb 2021
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 Ilana D Naiman Omri Azencot 108 11 0 15 Feb 2021
Accuracy and Architecture Studies of Residual Neural Network solving Ordinary Differential Equations Changxin Qiu Aaron Bendickson Joshua Kalyanapu Jue Yan 34 1 0 10 Jan 2021
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 A. Ramanathan Henglong Ma Akash Parvatikar C. Chennubhotla AI4CE 55 40 0 01 Dec 2020
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 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 Kadierdan Kaheman Steven L. Brunton J. Nathan Kutz 85 84 0 12 Sep 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
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 Haotian Feng P. Prabhakar 50 34 0 01 Jul 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
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 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 Kadierdan Kaheman J. Nathan Kutz Steven L. Brunton 76 275 0 05 Apr 2020
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 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 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 Zhen Chen Kailiang Wu D. Xiu 55 3 0 05 Mar 2020
Forecasting Sequential Data using Consistent Koopman Autoencoders Omri Azencot N. Benjamin Erichson Vanessa Lin Michael W. Mahoney AI4TS AI4CE 206 152 0 04 Mar 2020
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 W. Gilpin AI4TS 41 3 0 14 Feb 2020