Communities
Connect sessions
AI calendar
Organizations
Join Slack
Contact Sales
Search
Open menu
Home
Papers
1804.04272
Cited By
v1
v2 (latest)
Deep Neural Networks Motivated by Partial Differential Equations
12 April 2018
Lars Ruthotto
E. Haber
AI4CE
Re-assign community
ArXiv (abs)
PDF
HTML
Papers citing
"Deep Neural Networks Motivated by Partial Differential Equations"
50 / 244 papers shown
Riemannian Residual Neural Networks
Isay Katsman
Eric Chen
Sidhanth Holalkere
Anna Asch
Aaron Lou
Ser-Nam Lim
Christopher De Sa
251
21
0
16 Oct 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
870
19
0
08 Oct 2023
A Spectral Approach for Learning Spatiotemporal Neural Differential Equations
Mingtao Xia
Xiangting Li
Qijing Shen
Tom Chou
158
0
0
28 Sep 2023
Deep Learning in Deterministic Computational Mechanics
L. Herrmann
Stefan Kollmannsberger
AI4CE
PINN
313
1
0
27 Sep 2023
OS-net: Orbitally Stable Neural Networks
M. Ngom
Carlo Graziani
132
0
0
26 Sep 2023
Anisotropic Diffusion Stencils: From Simple Derivations over Stability Estimates to ResNet Implementations
Karl Schrader
Joachim Weickert
Michael Krause
DiffM
185
0
0
11 Sep 2023
Separable Hamiltonian Neural Networks
Zi-Yu Khoo
Dawen Wu
Jonathan Sze Choong Low
Stéphane Bressan
322
2
0
03 Sep 2023
A Novel Convolutional Neural Network Architecture with a Continuous Symmetry
CAAI International Conference on Artificial Intelligence (ICCAI), 2023
Y. Liu
Han-Juan Shao
Bing Bai
AI4CE
337
3
0
03 Aug 2023
Feature Transportation Improves Graph Neural Networks
AAAI Conference on Artificial Intelligence (AAAI), 2023
Moshe Eliasof
E. Haber
Eran Treister
GNN
277
21
0
29 Jul 2023
PottsMGNet: A Mathematical Explanation of Encoder-Decoder Based Neural Networks
SIAM Journal of Imaging Sciences (JSIS), 2023
X. Tai
Hao Liu
Raymond H. F. Chan
378
19
0
18 Jul 2023
Inverse Evolution Layers: Physics-informed Regularizers for Deep Neural Networks
Chao Liu
Zhonghua Qiao
Chong Li
Carola-Bibiane Schönlieb
224
0
0
14 Jul 2023
Multigrid-Augmented Deep Learning Preconditioners for the Helmholtz Equation using Compact Implicit Layers
SIAM Journal on Scientific Computing (SISC), 2023
Bar Lerer
Ido Ben-Yair
Eran Treister
AI4CE
338
7
0
30 Jun 2023
Designing Stable Neural Networks using Convex Analysis and ODEs
Ferdia Sherry
E. Celledoni
Matthias Joachim Ehrhardt
Davide Murari
B. Owren
Carola-Bibiane Schönlieb
307
16
0
29 Jun 2023
Time Regularization in Optimal Time Variable Learning
Pamm (PAMM), 2023
Evelyn Herberg
Roland A. Herzog
Frederik Köhne
AI4TS
AI4CE
92
1
0
28 Jun 2023
Learning Latent Dynamics via Invariant Decomposition and (Spatio-)Temporal Transformers
Kai Lagemann
C. Lagemann
Swarnava Mukherjee
271
2
0
21 Jun 2023
A Note on Dimensionality Reduction in Deep Neural Networks using Empirical Interpolation Method
Harbir Antil
Madhu Gupta
Randy Price
119
2
0
16 May 2023
Analysis of Numerical Integration in RNN-Based Residuals for Fault Diagnosis of Dynamic Systems
IFAC-PapersOnLine (IFAC-PapersOnLine), 2023
Arman Mohammadi
Theodor Westny
Daniel E. Jung
Mattias Krysander
182
9
0
08 May 2023
Predictions Based on Pixel Data: Insights from PDEs and Finite Differences
Journal of Computational Physics (JCP), 2023
E. Celledoni
James Jackaman
Davide Murari
B. Owren
324
2
0
01 May 2023
Pseudo-Hamiltonian neural networks for learning partial differential equations
Journal of Computational Physics (JCP), 2023
Sølve Eidnes
K. Lye
368
13
0
27 Apr 2023
Neural Delay Differential Equations: System Reconstruction and Image Classification
International Conference on Learning Representations (ICLR), 2021
Qunxi Zhu
Yao Guo
Wei Lin
174
39
0
11 Apr 2023
DRIP: Deep Regularizers for Inverse Problems
Inverse Problems (IP), 2023
Moshe Eliasof
E. Haber
Eran Treister
345
9
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
147
17
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
440
32
0
08 Mar 2023
Learning Hamiltonian Systems with Mono-Implicit Runge-Kutta Methods
International Conference on Geometric Science of Information (GSI), 2023
Haakon Noren
192
3
0
07 Mar 2023
Efficiency 360: Efficient Vision Transformers
Badri N. Patro
Vijay Srinivas Agneeswaran
406
7
0
16 Feb 2023
CQnet: convex-geometric interpretation and constraining neural-network trajectories
Bas Peters
251
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
189
3
0
02 Feb 2023
Modelling Long Range Dependencies in
N
N
N
D: From Task-Specific to a General Purpose CNN
International Conference on Learning Representations (ICLR), 2023
David M. Knigge
David W. Romero
Albert Gu
E. Gavves
Erik J. Bekkers
Jakub M. Tomczak
Mark Hoogendoorn
Jan-Jakob Sonke
3DV
214
28
0
25 Jan 2023
Improved generalization with deep neural operators for engineering systems: Path towards digital twin
Engineering applications of artificial intelligence (Eng. Appl. Artif. Intell.), 2023
Kazuma Kobayashi
James Daniell
S. B. Alam
AI4CE
252
41
0
17 Jan 2023
Continuous Depth Recurrent Neural Differential Equations
Srinivas Anumasa
Geetakrishnasai Gunapati
P. K. Srijith
AI4TS
146
1
0
28 Dec 2022
Deep Learning Methods for Partial Differential Equations and Related Parameter Identification Problems
Inverse Problems (IP), 2022
Derick Nganyu Tanyu
Jianfeng Ning
Tom Freudenberg
Nick Heilenkötter
A. Rademacher
U. Iben
Peter Maass
AI4CE
276
57
0
06 Dec 2022
Moving Frame Net: SE(3)-Equivariant Network for Volumes
Mateus Sangalli
S. Blusseau
Santiago Velasco-Forero
Jesús Angulo
228
8
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
148
0
0
25 Oct 2022
PDEBENCH: An Extensive Benchmark for Scientific Machine Learning
Neural Information Processing Systems (NeurIPS), 2022
M. Takamoto
T. Praditia
Raphael Leiteritz
Dan MacKinlay
Francesco Alesiani
Dirk Pflüger
Mathias Niepert
AI4CE
615
333
0
13 Oct 2022
Dynamical systems' based neural networks
E. Celledoni
Davide Murari
B. Owren
Carola-Bibiane Schönlieb
Ferdia Sherry
OOD
336
13
0
05 Oct 2022
Neural Generalized Ordinary Differential Equations with Layer-varying Parameters
Journal of Data Science (JDS), 2022
Duo Yu
Hongyu Miao
Hulin Wu
175
5
0
21 Sep 2022
STDEN: Towards Physics-Guided Neural Networks for Traffic Flow Prediction
AAAI Conference on Artificial Intelligence (AAAI), 2022
Jiahao Ji
Jingyuan Wang
Zhe Jiang
Jiawei Jiang
Hu Zhang
DiffM
PINN
OOD
AI4CE
292
99
0
01 Sep 2022
Estimating a potential without the agony of the partition function
SIAM Journal on Mathematics of Data Science (SIMODS), 2022
E. Haber
Moshe Eliasof
L. Tenorio
272
2
0
19 Aug 2022
Physics-Informed Deep Neural Operator Networks
S. Goswami
Aniruddha Bora
Yue Yu
George Karniadakis
PINN
AI4CE
309
156
0
08 Jul 2022
Zero Stability Well Predicts Performance of Convolutional Neural Networks
AAAI Conference on Artificial Intelligence (AAAI), 2022
Liangming Chen
Long Jin
Mingsheng Shang
MLT
258
8
0
27 Jun 2022
Learning the parameters of a differential equation from its trajectory via the adjoint equation
Social Science Research Network (SSRN), 2022
I. Fekete
A. Molnár
P. Simon
55
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
158
2
0
07 Jun 2022
A PDE-based Explanation of Extreme Numerical Sensitivities and Edge of Stability in Training Neural Networks
Journal of machine learning research (JMLR), 2022
Yuxin Sun
Dong Lao
G. Sundaramoorthi
A. Yezzi
419
2
0
04 Jun 2022
A memory-efficient neural ODE framework based on high-level adjoint differentiation
IEEE Transactions on Artificial Intelligence (IEEE TAI), 2022
Hong Zhang
Wenjun Zhao
238
6
0
02 Jun 2022
Bayesian Learning to Discover Mathematical Operations in Governing Equations of Dynamic Systems
Hongpeng Zhou
W. Pan
149
6
0
01 Jun 2022
Do Residual Neural Networks discretize Neural Ordinary Differential Equations?
Neural Information Processing Systems (NeurIPS), 2022
Michael E. Sander
Pierre Ablin
Gabriel Peyré
274
34
0
29 May 2022
Multi-resolution partial differential equations preserved learning framework for spatiotemporal dynamics
Communications Physics (Commun. Phys.), 2022
Xin-Yang Liu
Min Zhu
Lu Lu
Hao Sun
Jian-Xun Wang
PINN
AI4CE
254
72
0
09 May 2022
An Optimal Time Variable Learning Framework for Deep Neural Networks
Annals of Mathematical Sciences and Applications (AMSA), 2022
Harbir Antil
Hugo Díaz
Evelyn Herberg
119
4
0
18 Apr 2022
Learning time-dependent PDE solver using Message Passing Graph Neural Networks
Pourya Pilva
A. Zareei
AI4CE
145
11
0
15 Apr 2022
ODE Transformer: An Ordinary Differential Equation-Inspired Model for Sequence Generation
Annual Meeting of the Association for Computational Linguistics (ACL), 2022
Bei Li
Quan Du
Tao Zhou
Yi Jing
Shuhan Zhou
Xin Zeng
Tong Xiao
JingBo Zhu
Xuebo Liu
Min Zhang
201
41
0
17 Mar 2022
Previous
1
2
3
4
5
Next