Deep Neural Networks Motivated by Partial Differential Equations

12 April 2018

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

50 / 76 papers shown

Title
Geometric Fault-Tolerant Neural Network Tracking Control of Unknown Systems on Matrix Lie Groups Robin Chhabra Farzaneh Abdollahi 31 0 0 07 May 2025
Monotone Peridynamic Neural Operator for Nonlinear Material Modeling with Conditionally Unique Solutions Jihong Wang Xiaochuan Tian Zhongqiang Zhang Stewart Silling S. Jafarzadeh Yue Yu 39 0 0 02 May 2025
DISCO: learning to DISCover an evolution Operator for multi-physics-agnostic prediction Rudy Morel Jiequn Han Edouard Oyallon AI4CE 53 0 0 28 Apr 2025
OT-Transformer: A Continuous-time Transformer Architecture with Optimal Transport Regularization Kelvin Kan Xingjian Li Stanley Osher 91 2 0 30 Jan 2025
Scale generalisation properties of extended scale-covariant and scale-invariant Gaussian derivative networks on image datasets with spatial scaling variations Andrzej Perzanowski Tony Lindeberg 45 1 0 17 Sep 2024
Learning Regularization for Graph Inverse Problems Moshe Eliasof Md Shahriar Rahim Siddiqui Carola-Bibiane Schönlieb Eldad Haber GNN 34 0 0 19 Aug 2024
Graph Neural Reaction Diffusion Models Moshe Eliasof Eldad Haber Eran Treister DiffM AI4CE 30 2 0 16 Jun 2024
Deep Continuous Networks Nergis Tomen S. Pintea J. C. V. Gemert 92 14 0 02 Feb 2024
Accelerating Fractional PINNs using Operational Matrices of Derivative Tayebeh Taheri Alireza Afzal Aghaei Kourosh Parand 9 4 0 25 Jan 2024
Port-Hamiltonian Neural ODE Networks on Lie Groups For Robot Dynamics Learning and Control T. Duong Abdullah Altawaitan Jason Stanley Nikolay A. Atanasov 23 10 0 17 Jan 2024
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 18 9 0 08 Oct 2023
A Spectral Approach for Learning Spatiotemporal Neural Differential Equations Mingtao Xia Xiangting Li Qijing Shen Tom Chou 11 0 0 28 Sep 2023
PottsMGNet: A Mathematical Explanation of Encoder-Decoder Based Neural Networks X. Tai Hao Liu Raymond H. F. Chan 25 10 0 18 Jul 2023
Learning Latent Dynamics via Invariant Decomposition and (Spatio-)Temporal Transformers Kai Lagemann C. Lagemann Swarnava Mukherjee 34 2 0 21 Jun 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
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
Learning Hamiltonian Systems with Mono-Implicit Runge-Kutta Methods Haakon Noren 19 3 0 07 Mar 2023
Efficiency 360: Efficient Vision Transformers Badri N. Patro Vijay Srinivas Agneeswaran 21 6 0 16 Feb 2023
CQnet: convex-geometric interpretation and constraining neural-network trajectories B. Peters 24 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 18 3 0 02 Feb 2023
Continuous Depth Recurrent Neural Differential Equations Srinivas Anumasa Geetakrishnasai Gunapati P. K. Srijith AI4TS 18 0 0 28 Dec 2022
PDEBENCH: An Extensive Benchmark for Scientific Machine Learning M. Takamoto T. Praditia Raphael Leiteritz Dan MacKinlay Francesco Alesiani Dirk Pflüger Mathias Niepert AI4CE 22 201 0 13 Oct 2022
Dynamical systems' based neural networks E. Celledoni Davide Murari B. Owren Carola-Bibiane Schönlieb Ferdia Sherry OOD 38 10 0 05 Oct 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 12 77 0 01 Sep 2022
Estimating a potential without the agony of the partition function E. Haber Moshe Eliasof L. Tenorio 25 2 0 19 Aug 2022
Zero Stability Well Predicts Performance of Convolutional Neural Networks Liangming Chen Long Jin Mingsheng Shang MLT 19 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 11 0 0 17 Jun 2022
Do Residual Neural Networks discretize Neural Ordinary Differential Equations? Michael E. Sander Pierre Ablin Gabriel Peyré 27 25 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 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
Learning continuous models for continuous physics Aditi S. Krishnapriyan A. Queiruga N. Benjamin Erichson Michael W. Mahoney AI4CE 21 32 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 18 10 0 11 Feb 2022
LyaNet: A Lyapunov Framework for Training Neural ODEs I. D. Rodriguez Aaron D. Ames Yisong Yue 33 49 0 05 Feb 2022
Imbedding Deep Neural Networks A. Corbett D. Kangin AI4TS 20 2 0 31 Jan 2022
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 30 22 0 14 Dec 2021
Characteristic Neural Ordinary Differential Equations Xingzi Xu Ali Hasan Khalil Elkhalil Jie Ding Vahid Tarokh BDL 21 3 0 25 Nov 2021
Constructing Neural Network-Based Models for Simulating Dynamical Systems Christian Møldrup Legaard Thomas Schranz G. Schweiger Ján Drgovna Basak Falay C. Gomes Alexandros Iosifidis M. Abkar P. Larsen PINN AI4CE 25 93 0 02 Nov 2021
Sinkformers: Transformers with Doubly Stochastic Attention Michael E. Sander Pierre Ablin Mathieu Blondel Gabriel Peyré 21 76 0 22 Oct 2021
Solving Image PDEs with a Shallow Network Pascal Getreuer P. Milanfar Xiyang Luo 24 1 0 15 Oct 2021
Kinematically consistent recurrent neural networks for learning inverse problems in wave propagation Wrik Mallik R. Jaiman J. Jelovica AI4CE 25 3 0 08 Oct 2021
slimTrain -- A Stochastic Approximation Method for Training Separable Deep Neural Networks Elizabeth Newman Julianne Chung Matthias Chung Lars Ruthotto 39 6 0 28 Sep 2021
Short-term traffic prediction using physics-aware neural networks M. Pereira Annika Lang Balázs Kulcsár 26 20 0 21 Sep 2021
Quantized Convolutional Neural Networks Through the Lens of Partial Differential Equations Ido Ben-Yair Gil Ben Shalom Moshe Eliasof Eran Treister MQ 16 5 0 31 Aug 2021
Designing Rotationally Invariant Neural Networks from PDEs and Variational Methods Tobias Alt Karl Schrader Joachim Weickert Pascal Peter M. Augustin 14 4 0 31 Aug 2021
m-RevNet: Deep Reversible Neural Networks with Momentum Duo Li Shangqi Gao 10 5 0 12 Aug 2021
Bridging the Gap between Spatial and Spectral Domains: A Unified Framework for Graph Neural Networks Zhiqian Chen Fanglan Chen Lei Zhang Taoran Ji Kaiqun Fu Liang Zhao Feng Chen Lingfei Wu Charu C. Aggarwal Chang-Tien Lu 36 18 0 21 Jul 2021
Cell-average based neural network method for hyperbolic and parabolic partial differential equations Changxin Qiu Jue Yan 14 10 0 02 Jul 2021
Residual Networks as Flows of Velocity Fields for Diffeomorphic Time Series Alignment Hao Huang Boulbaba Ben Amor Xichan Lin Fan Zhu Yi Fang AI4TS MedIm 6 6 0 22 Jun 2021
Stateful ODE-Nets using Basis Function Expansions A. Queiruga N. Benjamin Erichson Liam Hodgkinson Michael W. Mahoney 27 16 0 21 Jun 2021