Normalizing field flows: Solving forward and inverse stochastic differential equations using physics-informed flow models

30 August 2021

Papers citing "Normalizing field flows: Solving forward and inverse stochastic differential equations using physics-informed flow models"

27 / 27 papers shown

Title
Scalable physics-informed deep generative model for solving forward and inverse stochastic differential equations Shaoqian Zhou Wen You Ling Guo Xuhui Meng DiffM MedIm 51 0 0 23 Mar 2025
Flow-based Bayesian filtering for high-dimensional nonlinear stochastic dynamical systems Xintong Wang Xiaofei Guan Ling Guo Hao Wu BDL 53 0 0 22 Feb 2025
TRADE: Transfer of Distributions between External Conditions with Normalizing Flows Stefan Wahl Armand Rousselot Felix Dräxler Ullrich Kothe Ullrich Köthe 29 0 0 25 Oct 2024
Towards Gaussian Process for operator learning: an uncertainty aware resolution independent operator learning algorithm for computational mechanics Sawan Kumar R. Nayek Souvik Chakraborty 30 1 0 17 Sep 2024
PinnDE: Physics-Informed Neural Networks for Solving Differential Equations Jason Matthews Alex Bihlo PINN 42 1 0 19 Aug 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 63 0 0 17 Jun 2024
Conditional Pseudo-Reversible Normalizing Flow for Surrogate Modeling in Quantifying Uncertainty Propagation Minglei Yang Pengjun Wang Ming Fan Dan Lu Yanzhao Cao Guannan Zhang AI4CE 27 1 0 31 Mar 2024
Score-Based Physics-Informed Neural Networks for High-Dimensional Fokker-Planck Equations Zheyuan Hu Zhongqiang Zhang George Karniadakis Kenji Kawaguchi 61 12 0 12 Feb 2024
Resolution invariant deep operator network for PDEs with complex geometries Jianguo Huang Yue Qiu 30 0 0 01 Feb 2024
Diffusion-Model-Assisted Supervised Learning of Generative Models for Density Estimation Yanfang Liu Minglei Yang Zezhong Zhang Feng Bao Yanzhao Cao Guannan Zhang 19 15 0 22 Oct 2023
PI-VEGAN: Physics Informed Variational Embedding Generative Adversarial Networks for Stochastic Differential Equations R. Gao Yufeng Wang Min Yang Chuanjun Chen GAN 34 2 0 21 Jul 2023
Bounded KRnet and its applications to density estimation and approximation Lisheng Zeng Xiaoliang Wan Tao Zhou 25 5 0 15 May 2023
Efficient Bayesian inference using physics-informed invertible neural networks for inverse problems Xiaofei Guan Xintong Wang Hao Wu Zihao Yang Peng Yu PINN 22 10 0 25 Apr 2023
Physics-Informed Deep Learning For Traffic State Estimation: A Survey and the Outlook Xuan Di Rongye Shi Zhaobin Mo Yongjie Fu PINN AI4TS AI4CE 29 28 0 03 Mar 2023
IB-UQ: Information bottleneck based uncertainty quantification for neural function regression and neural operator learning Ling Guo Hao Wu Wenwen Zhou Yan Wang Tao Zhou UQCV 18 11 0 07 Feb 2023
L-HYDRA: Multi-Head Physics-Informed Neural Networks Zongren Zou George Karniadakis AI4CE 18 26 0 05 Jan 2023
MC-Nonlocal-PINNs: handling nonlocal operators in PINNs via Monte Carlo sampling Xiaodong Feng Yue Qian W. Shen 17 3 0 26 Dec 2022
Taming Hyperparameter Tuning in Continuous Normalizing Flows Using the JKO Scheme Alexander Vidal Samy Wu Fung Luis Tenorio Stanley Osher L. Nurbekyan 32 15 0 30 Nov 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 15 5 0 26 Oct 2022
Less Emphasis on Difficult Layer Regions: Curriculum Learning for Singularly Perturbed Convection-Diffusion-Reaction Problems Yufeng Wang Cong Xu Min Yang Jin Zhang 11 4 0 23 Oct 2022
Bayesian deep learning framework for uncertainty quantification in high dimensions Jeahan Jung Minseok Choi BDL UQCV 18 1 0 21 Oct 2022
Failure-informed adaptive sampling for PINNs Zhiwei Gao Liang Yan Tao Zhou 18 77 0 01 Oct 2022
Fully probabilistic deep models for forward and inverse problems in parametric PDEs A. Vadeboncoeur Ömer Deniz Akyildiz Ieva Kazlauskaite Mark Girolami F. Cirak AI4CE 23 17 0 09 Aug 2022
TrafficFlowGAN: Physics-informed Flow based Generative Adversarial Network for Uncertainty Quantification Zhaobin Mo Yongjie Fu Daran Xu Xuan Di AI4CE 19 17 0 19 Jun 2022
A survey of unsupervised learning methods for high-dimensional uncertainty quantification in black-box-type problems Katiana Kontolati Dimitrios Loukrezis D. D. Giovanis Lohit Vandanapu Michael D. Shields 27 40 0 09 Feb 2022
Solving time dependent Fokker-Planck equations via temporal normalizing flow Xiaodong Feng Li Zeng Tao Zhou AI4CE 36 25 0 28 Dec 2021
hp-VPINNs: Variational Physics-Informed Neural Networks With Domain Decomposition E. Kharazmi Zhongqiang Zhang George Karniadakis 128 508 0 11 Mar 2020