PDE-Net 2.0: Learning PDEs from Data with A Numeric-Symbolic Hybrid Deep Network

30 November 2018

Papers citing "PDE-Net 2.0: Learning PDEs from Data with A Numeric-Symbolic Hybrid Deep Network"

50 / 84 papers shown

Title
UniSymNet: A Unified Symbolic Network Guided by Transformer Xinxin Li Juan Zhang Da Li Xingyu Liu Jin Xu Junping Yin 29 0 0 09 May 2025
PeSANet: Physics-encoded Spectral Attention Network for Simulating PDE-Governed Complex Systems Han Wan Rui Zhang Qi Wang Y. Liu Hao Sun PINN 45 0 0 03 May 2025
Plug-and-Play Physics-informed Learning using Uncertainty Quantified Port-Hamiltonian Models Kaiyuan Tan Peilun Li J. Wang Thomas Beckers AI4CE 17 0 0 24 Apr 2025
PIMRL: Physics-Informed Multi-Scale Recurrent Learning for Spatiotemporal Prediction Han Wan Qi Wang Hao Sun Hao Sun AI4CE 51 0 0 13 Mar 2025
Data-Efficient Kernel Methods for Learning Differential Equations and Their Solution Operators: Algorithms and Error Analysis Yasamin Jalalian Juan Felipe Osorio Ramirez Alexander W. Hsu Bamdad Hosseini H. Owhadi 43 0 0 02 Mar 2025
Adaptive parameters identification for nonlinear dynamics using deep permutation invariant networks Mouad Elaarabi Domenico Borzacchiello Yves Le Guennec Philippe Le Bot Sebastien Comas-Cardona 73 0 0 20 Jan 2025
Neural Port-Hamiltonian Differential Algebraic Equations for Compositional Learning of Electrical Networks Cyrus Neary Nathan Tsao Ufuk Topcu 72 1 0 15 Dec 2024
From Fourier to Neural ODEs: Flow Matching for Modeling Complex Systems Xin Li Jingdong Zhang Qunxi Zhu Chengli Zhao Xue Zhang Xiaojun Duan Wei Lin 44 3 0 19 May 2024
Towards General Neural Surrogate Solvers with Specialized Neural Accelerators Chenkai Mao Robert Lupoiu Tianxiang Dai Mingkun Chen Jonathan A. Fan AI4CE 36 4 0 02 May 2024
Data-Driven Discovery of PDEs via the Adjoint Method Mohsen Sadr Tony Tohme Kamal Youcef-Toumi PINN 19 1 0 30 Jan 2024
Physics-informed Deep Learning to Solve Three-dimensional Terzaghi Consolidation Equation: Forward and Inverse Problems Biao Yuan Ana Heitor He Wang Xiaohui Chen AI4CE PINN 31 1 0 08 Jan 2024
Hybrid Modeling Design Patterns Maja Rudolph Stefan Kurz Barbara Rakitsch AI4CE 28 8 0 29 Dec 2023
GIT-Net: Generalized Integral Transform for Operator Learning Chao Wang Alexandre H. Thiery AI4CE 26 0 0 05 Dec 2023
Physics-aware Machine Learning Revolutionizes Scientific Paradigm for Machine Learning and Process-based Hydrology Qingsong Xu Yilei Shi Jonathan Bamber Ye Tuo Ralf Ludwig Xiao Xiang Zhu AI4CE 20 9 0 08 Oct 2023
A Spectral Approach for Learning Spatiotemporal Neural Differential Equations Mingtao Xia Xiangting Li Qijing Shen Tom Chou 13 0 0 28 Sep 2023
Latent assimilation with implicit neural representations for unknown dynamics Zhuoyuan Li Bin Dong Pingwen Zhang AI4CE 22 3 0 18 Sep 2023
Learning to simulate partially known spatio-temporal dynamics with trainable difference operators Xiang Huang Zhuoyuan Li Hongsheng Liu Zidong Wang Hongye Zhou Bin Dong Bei Hua AI4TS AI4CE 27 1 0 26 Jul 2023
Flow Map Learning for Unknown Dynamical Systems: Overview, Implementation, and Benchmarks V. Churchill D. Xiu AI4CE 20 10 0 20 Jul 2023
A Bayesian Framework for learning governing Partial Differential Equation from Data K. More Tapas Tripura R. Nayek S. Chakraborty 16 10 0 08 Jun 2023
Discovering Causal Relations and Equations from Data Gustau Camps-Valls Andreas Gerhardus Urmi Ninad Gherardo Varando Georg Martius E. Balaguer-Ballester Ricardo Vinuesa Emiliano Díaz L. Zanna Jakob Runge PINN AI4Cl AI4CE CML 35 72 0 21 May 2023
Pseudo-Hamiltonian neural networks for learning partial differential equations Sølve Eidnes K. Lye 18 10 0 27 Apr 2023
Neural Delay Differential Equations: System Reconstruction and Image Classification Qunxi Zhu Yao Guo Wei Lin 15 31 0 11 Apr 2023
Machine Learning for Partial Differential Equations Steven L. Brunton J. Nathan Kutz AI4CE 37 20 0 30 Mar 2023
CONFIDE: Contextual Finite Differences Modelling of PDEs Ori Linial Orly Avner Dotan Di Castro 38 0 0 28 Mar 2023
GNN-based physics solver for time-independent PDEs R. J. Gladstone H. Rahmani V. Suryakumar Hadi Meidani M. DÉlia A. Zareei AI4CE 20 15 0 28 Mar 2023
Neural Partial Differential Equations with Functional Convolution Z. Wu Xingzhe He Yijun Li Cheng Yang Rui Liu S. Xiong Bo Zhu 23 1 0 10 Mar 2023
Physics-Informed Neural Networks for Prognostics and Health Management of Lithium-Ion Batteries Pengfei Wen Z. Ye Yong Li Shaowei Chen Pu Xie Shuai Zhao 30 35 0 02 Jan 2023
Interpretability and accessibility of machine learning in selected food processing, agriculture and health applications N. Ranasinghe A. Ramanan S. Fernando P. N. Hameed D. Herath T. Malepathirana P. Suganthan M. Niranjan Saman K. Halgamuge 8 2 0 30 Nov 2022
Discovering ordinary differential equations that govern time-series Soren Becker M. Klein Alexander Neitz Giambattista Parascandolo Niki Kilbertus AI4TS 19 4 0 05 Nov 2022
DISCOVER: Deep identification of symbolically concise open-form PDEs via enhanced reinforcement-learning Mengge Du Yuntian Chen Dong-juan Zhang 28 0 0 04 Oct 2022
Minimax Optimal Kernel Operator Learning via Multilevel Training Jikai Jin Yiping Lu Jose H. Blanchet Lexing Ying 20 11 0 28 Sep 2022
Data-driven, multi-moment fluid modeling of Landau damping Wenjie Cheng H. Fu Liang Wang C. Dong Yaqiu Jin M. Jiang Jiayu Ma Yilan Qin Kexin Liu PINN AI4CE 22 12 0 10 Sep 2022
D-CIPHER: Discovery of Closed-form Partial Differential Equations Krzysztof Kacprzyk Zhaozhi Qian M. Schaar AI4CE 21 1 0 21 Jun 2022
Sobolev Acceleration and Statistical Optimality for Learning Elliptic Equations via Gradient Descent Yiping Lu Jose H. Blanchet Lexing Ying 32 7 0 15 May 2022
Automated differential equation solver based on the parametric approximation optimization A. Hvatov Tatiana Tikhonova 14 4 0 11 May 2022
Multi-resolution partial differential equations preserved learning framework for spatiotemporal dynamics Xin-Yang Liu Min Zhu Lu Lu Hao Sun Jian-Xun Wang PINN AI4CE 28 45 0 09 May 2022
Learning time-dependent PDE solver using Message Passing Graph Neural Networks Pourya Pilva A. Zareei AI4CE 25 7 0 15 Apr 2022
PARC: Physics-Aware Recurrent Convolutional Neural Networks to Assimilate Meso-scale Reactive Mechanics of Energetic Materials Phong C. H. Nguyen Y. Nguyen Joseph B. Choi P. Seshadri H. Udaykumar Stephen Seung-Yeob Baek AI4CE 16 16 0 04 Apr 2022
When Physics Meets Machine Learning: A Survey of Physics-Informed Machine Learning Chuizheng Meng Sungyong Seo Defu Cao Sam Griesemer Yan Liu PINN AI4CE 36 55 0 31 Mar 2022
Online Weak-form Sparse Identification of Partial Differential Equations Daniel Messenger E. Dall’Anese David M. Bortz 41 13 0 08 Mar 2022
Robust Modeling of Unknown Dynamical Systems via Ensemble Averaged Learning V. Churchill Steve Manns Zhen Chen D. Xiu AI4CE 23 8 0 07 Mar 2022
Modeling unknown dynamical systems with hidden parameters Xiaohan Fu Weize Mao L. Chang D. Xiu 16 5 0 03 Feb 2022
Discovering Nonlinear PDEs from Scarce Data with Physics-encoded Learning Chengping Rao Pu Ren Yang Liu Hao-Lun Sun AI4CE 43 26 0 28 Jan 2022
Characteristic Neural Ordinary Differential Equations Xingzi Xu Ali Hasan Khalil Elkhalil Jie Ding Vahid Tarokh BDL 21 3 0 25 Nov 2021
NeuralPDE: Modelling Dynamical Systems from Data Andrzej Dulny Andreas Hotho Anna Krause AI4CE 22 11 0 15 Nov 2021
DeepParticle: learning invariant measure by a deep neural network minimizing Wasserstein distance on data generated from an interacting particle method Zhongjian Wang Jack Xin Zhiwen Zhang 39 15 0 02 Nov 2021
Short-term traffic prediction using physics-aware neural networks M. Pereira Annika Lang Balázs Kulcsár 26 20 0 21 Sep 2021
Physics-integrated hybrid framework for model form error identification in nonlinear dynamical systems Shailesh Garg S. Chakraborty B. Hazra 41 20 0 01 Sep 2021
Designing Rotationally Invariant Neural Networks from PDEs and Variational Methods Tobias Alt Karl Schrader Joachim Weickert Pascal Peter M. Augustin 22 4 0 31 Aug 2021
Data-Driven Constitutive Relation Reveals Scaling Law for Hydrodynamic Transport Coefficients Candi Zheng Yang Wang Shiying Chen 14 4 0 01 Aug 2021