Solving for high dimensional committor functions using artificial neural networks

28 February 2018

Papers citing "Solving for high dimensional committor functions using artificial neural networks"

50 / 51 papers shown

Title
Estimating Committor Functions via Deep Adaptive Sampling on Rare Transition Paths Yueyang Wang Kejun Tang Xili Wang Xiaoliang Wan Weiqing Ren Chao Yang 40 0 0 28 Jan 2025
The fast committor machine: Interpretable prediction with kernels D. Aristoff Mats S. Johnson Gideon Simpson Robert J. Webber 26 5 0 16 May 2024
Deep Learning Method for Computing Committor Functions with Adaptive Sampling Bo Lin Weiqing Ren 23 3 0 09 Apr 2024
Computing Transition Pathways for the Study of Rare Events Using Deep Reinforcement Learning Bo Lin Yangzheng Zhong Weiqing Ren 11 0 0 08 Apr 2024
Accelerated Sampling of Rare Events using a Neural Network Bias Potential Xinru Hua R. Ahmad Jose Blanchet Wei Cai AI4CE 82 3 0 13 Jan 2024
Randomized Sparse Neural Galerkin Schemes for Solving Evolution Equations with Deep Networks Jules Berman Benjamin Peherstorfer 26 13 0 07 Oct 2023
Diffusion Methods for Generating Transition Paths Luke Triplett Jianfeng Lu 17 5 0 19 Sep 2023
Coupling parameter and particle dynamics for adaptive sampling in Neural Galerkin schemes Yuxiao Wen Eric Vanden-Eijnden Benjamin Peherstorfer 24 12 0 27 Jun 2023
A Finite Expression Method for Solving High-Dimensional Committor Problems Zezheng Song M. Cameron Haizhao Yang 16 6 0 21 Jun 2023
Probing reaction channels via reinforcement learning Senwei Liang Aditya Singh Yuanran Zhu David T. Limmer Chao Yang 23 6 0 27 May 2023
GPT-PINN: Generative Pre-Trained Physics-Informed Neural Networks toward non-intrusive Meta-learning of parametric PDEs Yanlai Chen Shawn Koohy PINN AI4CE 34 24 0 27 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 J. Weare 17 9 0 22 Mar 2023
Computing non-equilibrium trajectories by a deep learning approach E. Simonnet AI4CE 27 6 0 08 Oct 2022
Minimax Optimal Kernel Operator Learning via Multilevel Training Jikai Jin Yiping Lu Jose H. Blanchet Lexing Ying 23 11 0 28 Sep 2022
Adaptive importance sampling based on fault tree analysis for piecewise deterministic Markov process G. Chennetier Hassane Chraïbi A. Dutfoy Josselin Garnier 32 2 0 17 Sep 2022
The Mori-Zwanzig formulation of deep learning D. Venturi Xiantao Li 20 1 0 12 Sep 2022
Approximation of Functionals by Neural Network without Curse of Dimensionality Yahong Yang Yang Xiang 26 6 0 28 May 2022
Neural Galerkin Schemes with Active Learning for High-Dimensional Evolution Equations Joan Bruna Benjamin Peherstorfer Eric Vanden-Eijnden 19 60 0 02 Mar 2022
Interpolating between BSDEs and PINNs: deep learning for elliptic and parabolic boundary value problems Nikolas Nusken Lorenz Richter PINN DiffM 31 27 0 07 Dec 2021
Computing the Invariant Distribution of Randomly Perturbed Dynamical Systems Using Deep Learning Bo Lin Qianxiao Li W. Ren 23 8 0 22 Oct 2021
Spline-PINN: Approaching PDEs without Data using Fast, Physics-Informed Hermite-Spline CNNs Nils Wandel Michael Weinmann Michael Neidlin Reinhard Klein AI4CE 58 60 0 15 Sep 2021
Supervised Learning and the Finite-Temperature String Method for Computing Committor Functions and Reaction Rates Muhammad R Hasyim Clay H. Batton K. Mandadapu 19 10 0 28 Jul 2021
On the Representation of Solutions to Elliptic PDEs in Barron Spaces Ziang Chen Jianfeng Lu Yulong Lu 35 26 0 14 Jun 2021
Reinforcement learning of rare diffusive dynamics Avishek Das Dominic C. Rose J. P. Garrahan David T. Limmer 14 27 0 10 May 2021
A semigroup method for high dimensional elliptic PDEs and eigenvalue problems based on neural networks Haoya Li Lexing Ying 19 10 0 07 May 2021
Neural network architectures using min-plus algebra for solving certain high dimensional optimal control problems and Hamilton-Jacobi PDEs Jérome Darbon P. Dower Tingwei Meng 8 22 0 07 May 2021
A Priori Generalization Error Analysis of Two-Layer Neural Networks for Solving High Dimensional Schrödinger Eigenvalue Problems Jianfeng Lu Yulong Lu 34 29 0 04 May 2021
A Priori Generalization Analysis of the Deep Ritz Method for Solving High Dimensional Elliptic Equations Jianfeng Lu Yulong Lu Min Wang 36 37 0 05 Jan 2021
An overview on deep learning-based approximation methods for partial differential equations C. Beck Martin Hutzenthaler Arnulf Jentzen Benno Kuckuck 30 146 0 22 Dec 2020
Teaching the Incompressible Navier-Stokes Equations to Fast Neural Surrogate Models in 3D Nils Wandel Michael Weinmann Reinhard Klein AI4CE 26 50 0 22 Dec 2020
A semigroup method for high dimensional committor functions based on neural network Haoya Li Y. Khoo Yinuo Ren Lexing Ying 8 6 0 12 Dec 2020
Active Importance Sampling for Variational Objectives Dominated by Rare Events: Consequences for Optimization and Generalization Grant M. Rotskoff Andrew R. Mitchell Eric Vanden-Eijnden 6 13 0 11 Aug 2020
Two-Layer Neural Networks for Partial Differential Equations: Optimization and Generalization Theory Tao Luo Haizhao Yang 32 73 0 28 Jun 2020
Learning Incompressible Fluid Dynamics from Scratch -- Towards Fast, Differentiable Fluid Models that Generalize Nils Wandel Michael Weinmann Reinhard Klein AI4CE 19 8 0 15 Jun 2020
hp-VPINNs: Variational Physics-Informed Neural Networks With Domain Decomposition E. Kharazmi Zhongqiang Zhang George Karniadakis 125 508 0 11 Mar 2020
Integrating Scientific Knowledge with Machine Learning for Engineering and Environmental Systems J. Willard X. Jia Shaoming Xu M. Steinbach Vipin Kumar AI4CE 91 387 0 10 Mar 2020
On generalized residue network for deep learning of unknown dynamical systems Zhen Chen D. Xiu AI4CE 19 46 0 23 Jan 2020
Machine Learning from a Continuous Viewpoint E. Weinan Chao Ma Lei Wu 23 102 0 30 Dec 2019
Solving Inverse Wave Scattering with Deep Learning Yuwei Fan Lexing Ying 11 26 0 27 Nov 2019
Solving Traveltime Tomography with Deep Learning Yuwei Fan Lexing Ying 16 13 0 25 Nov 2019
Solving Optical Tomography with Deep Learning Yuwei Fan Lexing Ying 11 15 0 10 Oct 2019
Learning Everywhere: A Taxonomy for the Integration of Machine Learning and Simulations Geoffrey C. Fox S. Jha AI4CE 13 13 0 29 Sep 2019
Meta-learning Pseudo-differential Operators with Deep Neural Networks Jordi Feliu-Fabà Yuwei Fan Lexing Ying 14 39 0 16 Jun 2019
Computing Committor Functions for the Study of Rare Events Using Deep Learning Qianxiao Li Bo Lin W. Ren 14 67 0 14 Jun 2019
Modeling the Dynamics of PDE Systems with Physics-Constrained Deep Auto-Regressive Networks N. Geneva N. Zabaras AI4CE 10 268 0 13 Jun 2019
Solving Electrical Impedance Tomography with Deep Learning Yuwei Fan Lexing Ying 12 100 0 06 Jun 2019
Neural Jump Stochastic Differential Equations J. Jia Austin R. Benson BDL 20 222 0 24 May 2019
Variational training of neural network approximations of solution maps for physical models Yingzhou Li Jianfeng Lu Anqi Mao GAN 17 35 0 07 May 2019
SwitchNet: a neural network model for forward and inverse scattering problems Y. Khoo Lexing Ying 20 132 0 23 Oct 2018
Butterfly-Net: Optimal Function Representation Based on Convolutional Neural Networks Yingzhou Li Xiuyuan Cheng Jianfeng Lu 21 23 0 18 May 2018