Solving Inverse Stochastic Problems from Discrete Particle Observations Using the Fokker-Planck Equation and Physics-informed Neural Networks

24 August 2020

Papers citing "Solving Inverse Stochastic Problems from Discrete Particle Observations Using the Fokker-Planck Equation and Physics-informed Neural Networks"

35 / 35 papers shown

Title
Time-dependent density estimation using binary classifiers Agnimitra Dasgupta Javier Murgoitio-Esandi Ali Fardisi Assad A. Oberai 12 0 0 18 Jun 2025
A Robust Model-Based Approach for Continuous-Time Policy Evaluation with Unknown Lévy Process Dynamics Qihao Ye Xiaochuan Tian Yuhua Zhu 95 1 0 02 Apr 2025
A Training-Free Conditional Diffusion Model for Learning Stochastic Dynamical Systems Yanfang Liu Yuán Chen Dongbin Xiu Guannan Zhang DiffM 82 4 0 04 Oct 2024
Data-driven Effective Modeling of Multiscale Stochastic Dynamical Systems Yuán Chen Dongbin Xiu 77 0 0 27 Aug 2024
Tackling the Curse of Dimensionality in Fractional and Tempered Fractional PDEs with Physics-Informed Neural Networks Zheyuan Hu Kenji Kawaguchi Zhongqiang Zhang George Karniadakis AI4CE 87 3 0 17 Jun 2024
Score-fPINN: Fractional Score-Based Physics-Informed Neural Networks for High-Dimensional Fokker-Planck-Levy Equations Zheyuan Hu Zhongqiang Zhang George Karniadakis Kenji Kawaguchi 88 0 0 17 Jun 2024
Neural McKean-Vlasov Processes: Distributional Dependence in Diffusion Processes Haoming Yang Ali Hasan Yuting Ng Vahid Tarokh DiffM 74 6 0 15 Apr 2024
Weak Collocation Regression for Inferring Stochastic Dynamics with Lévy Noise Liya Guo Liwei Lu Zhijun Zeng Pipi Hu Yi Zhu 96 1 0 13 Mar 2024
DynGMA: a robust approach for learning stochastic differential equations from data Aiqing Zhu Qianxiao Li OOD DiffM 87 4 0 22 Feb 2024
Score-Based Physics-Informed Neural Networks for High-Dimensional Fokker-Planck Equations Zheyuan Hu Zhongqiang Zhang George Karniadakis Kenji Kawaguchi 107 15 0 12 Feb 2024
Hutchinson Trace Estimation for High-Dimensional and High-Order Physics-Informed Neural Networks Zheyuan Hu Zekun Shi George Karniadakis Kenji Kawaguchi AI4CE PINN 134 27 0 22 Dec 2023
Inferring stochastic rates from heterogeneous snapshots of particle positions Christopher E Miles Scott A. McKinley Fangyuan Ding R. Lehoucq 30 6 0 08 Nov 2023
AI-Aristotle: A Physics-Informed framework for Systems Biology Gray-Box Identification Nazanin Ahmadi Daryakenari Mario De Florio K. Shukla George Karniadakis 97 34 0 29 Sep 2023
Physics-Informed Solution of The Stationary Fokker-Plank Equation for a Class of Nonlinear Dynamical Systems: An Evaluation Study H. Alhussein Mohammed Khasawneh M. Daqaq 53 1 0 25 Sep 2023
Learning Stochastic Dynamical System via Flow Map Operator Yuán Chen D. Xiu AI4CE 77 16 0 05 May 2023
Reservoir Computing with Error Correction: Long-term Behaviors of Stochastic Dynamical Systems Cheng Fang Yubin Lu Ting Gao Jinqiao Duan 43 4 0 01 May 2023
Maximum-likelihood Estimators in Physics-Informed Neural Networks for High-dimensional Inverse Problems G. S. Gusmão A. Medford PINN 52 9 0 12 Apr 2023
Drift Identification for Lévy alpha-Stable Stochastic Systems Harish S. Bhat 62 1 0 06 Dec 2022
$Adaptive deep density approximation for fractional Fokker-Planck equations$ Adaptive deep density approximation for fractional Fokker-Planck equations Li Zeng Xiaoliang Wan Tao Zhou 61 5 0 26 Oct 2022
Weak Collocation Regression method: fast reveal hidden stochastic dynamics from high-dimensional aggregate data Liwei Lu Zhijun Zeng Yan Jiang Yi Zhu Pipi Hu 70 4 0 06 Sep 2022
Revisiting PINNs: Generative Adversarial Physics-informed Neural Networks and Point-weighting Method Wensheng Li Chao Zhang Chuncheng Wang Hanting Guan Dacheng Tao DiffM PINN 74 12 0 18 May 2022
An Optimal Control Method to Compute the Most Likely Transition Path for Stochastic Dynamical Systems with Jumps Wei Wei Ting Gao Jinqiao Duan Xiaoli Chen 20 13 0 31 Mar 2022
An end-to-end deep learning approach for extracting stochastic dynamical systems with $α$ -stable Lévy noise Cheng Fang Yubin Lu Ting Gao Jinqiao Duan 87 16 0 31 Jan 2022
Temperature Field Inversion of Heat-Source Systems via Physics-Informed Neural Networks Xu Liu Wei Peng Zhiqiang Gong Weien Zhou Wen Yao 51 58 0 18 Jan 2022
Solving time dependent Fokker-Planck equations via temporal normalizing flow Xiaodong Feng Li Zeng Tao Zhou AI4CE 79 25 0 28 Dec 2021
Nonparametric inference of stochastic differential equations based on the relative entropy rate Min Dai Jinqiao Duan Jianyu Hu Xiangjun Wang 48 2 0 09 Dec 2021
Neural network stochastic differential equation models with applications to financial data forecasting Luxuan Yang Ting Gao Yubin Lu Jinqiao Duan Tao Liu AI4TS 84 41 0 25 Nov 2021
Computing the Invariant Distribution of Randomly Perturbed Dynamical Systems Using Deep Learning Bo Lin Qianxiao Li W. Ren 102 9 0 22 Oct 2021
Learning Mean-Field Equations from Particle Data Using WSINDy Daniel Messenger David M. Bortz 99 37 0 14 Oct 2021
Extracting stochastic dynamical systems with $α$ -stable Lévy noise from data Yang Li Yubin Lu Shengyuan Xu Jinqiao Duan 58 15 0 30 Sep 2021
Extracting Stochastic Governing Laws by Nonlocal Kramers-Moyal Formulas Yubin Lu Yang Li Jinqiao Duan 47 16 0 28 Aug 2021
Learning the temporal evolution of multivariate densities via normalizing flows Yubin Lu R. Maulik Ting Gao Felix Dietrich Ioannis G. Kevrekidis Jinqiao Duan 53 24 0 29 Jul 2021
Adaptive deep density approximation for Fokker-Planck equations Keju Tang Xiaoliang Wan Qifeng Liao 93 40 0 20 Mar 2021
Towards a mathematical theory of trajectory inference Hugo Lavenant Stephen X. Zhang Young-Heon Kim Geoffrey Schiebinger 50 41 0 18 Feb 2021
Learning Thermodynamically Stable and Galilean Invariant Partial Differential Equations for Non-equilibrium Flows Juntao Huang Zhiting Ma Y. Zhou W. Yong AI4CE 63 16 0 28 Sep 2020