v1v2 (latest)

Deep Neural Networks Motivated by Partial Differential Equations

12 April 2018

Papers citing "Deep Neural Networks Motivated by Partial Differential Equations"

50 / 228 papers shown

Title
Analysis of Numerical Integration in RNN-Based Residuals for Fault Diagnosis of Dynamic Systems Arman Mohammadi Theodor Westny Daniel E. Jung Mattias Krysander 52 5 0 08 May 2023
Predictions Based on Pixel Data: Insights from PDEs and Finite Differences E. Celledoni James Jackaman Davide Murari B. Owren 103 2 0 01 May 2023
Pseudo-Hamiltonian neural networks for learning partial differential equations Sølve Eidnes K. Lye 82 11 0 27 Apr 2023
Neural Delay Differential Equations: System Reconstruction and Image Classification Qunxi Zhu Yao Guo Wei Lin 71 33 0 11 Apr 2023
DRIP: Deep Regularizers for Inverse Problems Moshe Eliasof E. Haber Eran Treister 90 8 0 30 Mar 2023
GNN-based physics solver for time-independent PDEs R. J. Gladstone H. Rahmani V. Suryakumar Hadi Meidani M. DÉlia A. Zareei AI4CE 46 14 0 28 Mar 2023
Multilevel Diffusion: Infinite Dimensional Score-Based Diffusion Models for Image Generation Paul Hagemann Sophie Mildenberger Lars Ruthotto Gabriele Steidl Ni Yang DiffM 109 25 0 08 Mar 2023
Learning Hamiltonian Systems with Mono-Implicit Runge-Kutta Methods Haakon Noren 48 3 0 07 Mar 2023
Efficiency 360: Efficient Vision Transformers Badri N. Patro Vijay Srinivas Agneeswaran 151 6 0 16 Feb 2023
CQnet: convex-geometric interpretation and constraining neural-network trajectories Bas Peters 63 0 0 09 Feb 2023
Learning PDE Solution Operator for Continuous Modeling of Time-Series Yesom Park Jaemoo Choi Changyeon Yoon Changhoon Song Myung-joo Kang AI4TS AI4CE 33 3 0 02 Feb 2023
Modelling Long Range Dependencies in $N$ D: From Task-Specific to a General Purpose CNN David M. Knigge David W. Romero Albert Gu E. Gavves Erik J. Bekkers Jakub M. Tomczak Mark Hoogendoorn Jan-Jakob Sonke 3DV 91 22 0 25 Jan 2023
Improved generalization with deep neural operators for engineering systems: Path towards digital twin Kazuma Kobayashi James Daniell S. B. Alam AI4CE 67 23 0 17 Jan 2023
Continuous Depth Recurrent Neural Differential Equations Srinivas Anumasa Geetakrishnasai Gunapati P. K. Srijith AI4TS 46 1 0 28 Dec 2022
Deep Learning Methods for Partial Differential Equations and Related Parameter Identification Problems Derick Nganyu Tanyu Jianfeng Ning Tom Freudenberg Nick Heilenkötter A. Rademacher U. Iben Peter Maass AI4CE 92 35 0 06 Dec 2022
Moving Frame Net: SE(3)-Equivariant Network for Volumes Mateus Sangalli S. Blusseau Santiago Velasco-Forero Jesús Angulo 117 7 0 07 Nov 2022
FO-PINNs: A First-Order formulation for Physics Informed Neural Networks R. J. Gladstone M. A. Nabian N. Sukumar Ankit Srivastava Hadi Meidani PINN AI4CE 53 0 0 25 Oct 2022
PDEBENCH: An Extensive Benchmark for Scientific Machine Learning M. Takamoto T. Praditia Raphael Leiteritz Dan MacKinlay Francesco Alesiani Dirk Pflüger Mathias Niepert AI4CE 116 237 0 13 Oct 2022
Dynamical systems' based neural networks E. Celledoni Davide Murari B. Owren Carola-Bibiane Schönlieb Ferdia Sherry OOD 124 11 0 05 Oct 2022
Neural Generalized Ordinary Differential Equations with Layer-varying Parameters Duo Yu Hongyu Miao Hulin Wu 63 4 0 21 Sep 2022
STDEN: Towards Physics-Guided Neural Networks for Traffic Flow Prediction Jiahao Ji Jingyuan Wang Zhe Jiang Jiawei Jiang Hu Zhang DiffM PINN OOD AI4CE 88 81 0 01 Sep 2022
Estimating a potential without the agony of the partition function E. Haber Moshe Eliasof L. Tenorio 61 2 0 19 Aug 2022
Physics-Informed Deep Neural Operator Networks S. Goswami Aniruddha Bora Yue Yu George Karniadakis PINN AI4CE 107 109 0 08 Jul 2022
Zero Stability Well Predicts Performance of Convolutional Neural Networks Liangming Chen Long Jin Mingsheng Shang MLT 77 8 0 27 Jun 2022
Learning the parameters of a differential equation from its trajectory via the adjoint equation I. Fekete A. Molnár P. Simon 22 0 0 17 Jun 2022
On the balance between the training time and interpretability of neural ODE for time series modelling Yakov Golovanev A. Hvatov AI4TS 47 2 0 07 Jun 2022
A PDE-based Explanation of Extreme Numerical Sensitivities and Edge of Stability in Training Neural Networks Yuxin Sun Dong Lao G. Sundaramoorthi A. Yezzi 67 3 0 04 Jun 2022
A memory-efficient neural ODE framework based on high-level adjoint differentiation Hong Zhang Wenjun Zhao 62 5 0 02 Jun 2022
Bayesian Learning to Discover Mathematical Operations in Governing Equations of Dynamic Systems Hongpeng Zhou W. Pan 39 4 0 01 Jun 2022
Do Residual Neural Networks discretize Neural Ordinary Differential Equations? Michael E. Sander Pierre Ablin Gabriel Peyré 105 28 0 29 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 102 51 0 09 May 2022
An Optimal Time Variable Learning Framework for Deep Neural Networks Harbir Antil Hugo Díaz Evelyn Herberg 35 4 0 18 Apr 2022
Learning time-dependent PDE solver using Message Passing Graph Neural Networks Pourya Pilva A. Zareei AI4CE 61 7 0 15 Apr 2022
ODE Transformer: An Ordinary Differential Equation-Inspired Model for Sequence Generation Bei Li Quan Du Tao Zhou Yi Jing Shuhan Zhou Xin Zeng Tong Xiao JingBo Zhu Xuebo Liu Min Zhang 57 35 0 17 Mar 2022
Unraveled Multilevel Transformation Networks for Predicting Sparsely-Observed Spatiotemporal Dynamics Priyabrata Saha Saibal Mukhopadhyay 33 1 0 16 Mar 2022
Learning Deep Implicit Fourier Neural Operators (IFNOs) with Applications to Heterogeneous Material Modeling Huaiqian You Quinn Zhang Colton J. Ross Chung-Hao Lee Yue Yu AI4CE 102 107 0 15 Mar 2022
NINNs: Nudging Induced Neural Networks Harbir Antil R. Löhner Randy Price AI4CE 26 1 0 15 Mar 2022
FinNet: Solving Time-Independent Differential Equations with Finite Difference Neural Network Son N. T. Tu Thu Nguyen AI4CE 51 0 0 18 Feb 2022
Learning continuous models for continuous physics Aditi S. Krishnapriyan A. Queiruga N. Benjamin Erichson Michael W. Mahoney AI4CE 106 35 0 17 Feb 2022
Bounded nonlinear forecasts of partially observed geophysical systems with physics-constrained deep learning Said Ouala Steven L. Brunton A. Pascual Bertrand Chapron F. Collard L. Gaultier Ronan Fablet PINN AI4TS AI4CE 71 10 0 11 Feb 2022
LyaNet: A Lyapunov Framework for Training Neural ODEs I. D. Rodriguez Aaron D. Ames Yisong Yue 70 52 0 05 Feb 2022
Machine Learning in Heterogeneous Porous Materials Martha DÉli H. Deng Cedric G. Fraces K. Garikipati L. Graham‐Brady ... H. Tchelepi B. Važić Hari S. Viswanathan H. Yoon P. Zarzycki AI4CE 80 9 0 04 Feb 2022
Imbedding Deep Neural Networks A. Corbett D. Kangin AI4TS 49 2 0 31 Jan 2022
Convergence of Invariant Graph Networks Chen Cai Yusu Wang 109 4 0 25 Jan 2022
Nonlocal Kernel Network (NKN): a Stable and Resolution-Independent Deep Neural Network Huaiqian You Yue Yu M. DÉlia T. Gao Stewart Silling 100 74 0 06 Jan 2022
Neural Piecewise-Constant Delay Differential Equations Qunxi Zhu Yifei Shen Dongsheng Li Wei-Jer Lin PINN 64 7 0 04 Jan 2022
Latent Time Neural Ordinary Differential Equations Srinivas Anumasa P. K. Srijith BDL 36 5 0 23 Dec 2021
Neural Born Iteration Method For Solving Inverse Scattering Problems: 2D Cases Tao Shan Zhichao Lin Xiaoqian Song Maokun Li Fan Yang Zhensheng Xu 71 18 0 18 Dec 2021
Learning High-Dimensional Parametric Maps via Reduced Basis Adaptive Residual Networks Thomas O'Leary-Roseberry Xiaosong Du A. Chaudhuri J. Martins Karen E. Willcox Omar Ghattas 66 23 0 14 Dec 2021
Nonparametric inference of stochastic differential equations based on the relative entropy rate Min Dai Jinqiao Duan Jianyu Hu Xiangjun Wang 51 2 0 09 Dec 2021