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Deep Neural Networks Motivated by Partial Differential Equations
v1v2 (latest)

Deep Neural Networks Motivated by Partial Differential Equations

12 April 2018
Lars Ruthotto
E. Haber
    AI4CE
ArXiv (abs)PDFHTML

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

50 / 244 papers shown
Title
Reversing Large Language Models for Efficient Training and Fine-Tuning
Reversing Large Language Models for Efficient Training and Fine-Tuning
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Moshe Eliasof
Javier S. Turek
Uri M. Ascher
Eran Treister
Eldad Haber
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Mixed Precision Training of Neural ODEs
Mixed Precision Training of Neural ODEs
E. Celledoni
B. Owren
Lars Ruthotto
Tianjiao Nicole Yang
96
1
0
27 Oct 2025
Deep Neural ODE Operator Networks for PDEs
Deep Neural ODE Operator Networks for PDEs
Ziqian Li
Kang Liu
Yongcun Song
Hangrui Yue
Enrique Zuazua
AI4CE
149
0
0
17 Oct 2025
Neural Network approximation power on homogeneous and heterogeneous reaction-diffusion equations
Neural Network approximation power on homogeneous and heterogeneous reaction-diffusion equations
Haotian Feng
76
0
0
15 Oct 2025
Stability of Transformers under Layer Normalization
Stability of Transformers under Layer Normalization
Kelvin Kan
Xingjian Li
Benjamin J. Zhang
Tuhin Sahai
Stanley Osher
Krishna Kumar
Markos A. Katsoulakis
101
1
0
10 Oct 2025
Deep Neural Networks Inspired by Differential Equations
Deep Neural Networks Inspired by Differential Equations
Y. Liu
Lianfang Wang
Kuilin Qin
Qinghua Zhang
Faqiang Wang
Li-min Cui
Jun Liu
Yuping Duan
T. Zeng
AI4TSAI4CE
186
0
0
09 Oct 2025
A Mathematical Explanation of Transformers for Large Language Models and GPTs
A Mathematical Explanation of Transformers for Large Language Models and GPTs
X. Tai
Hao Liu
Lingfeng Li
Raymond H. F. Chan
AI4CE
146
1
0
05 Oct 2025
Mathematical Modeling and Convergence Analysis of Deep Neural Networks with Dense Layer Connectivities in Deep Learning
Mathematical Modeling and Convergence Analysis of Deep Neural Networks with Dense Layer Connectivities in Deep Learning
Jinshu Huang
Haibin Su
Xue-Cheng Tai
Chunlin Wu
AI4CE
101
0
0
02 Oct 2025
VNODE: A Piecewise Continuous Volterra Neural Network
VNODE: A Piecewise Continuous Volterra Neural Network
Siddharth Roheda
Aniruddha Bala
Rohit Chowdhury
Rohan Jaiswal
148
0
0
29 Sep 2025
SoC-DT: Standard-of-Care Aligned Digital Twins for Patient-Specific Tumor Dynamics
SoC-DT: Standard-of-Care Aligned Digital Twins for Patient-Specific Tumor Dynamics
Moinak Bhattacharya
Gagandeep Singh
Prateek Prasanna
140
0
0
29 Sep 2025
A Neural ODE Approach to Aircraft Flight Dynamics Modelling
A Neural ODE Approach to Aircraft Flight Dynamics Modelling
Gabriel Jarry
Ramon Dalmau
Xavier Olive
Philippe Very
AI4CE
61
1
0
27 Sep 2025
Wavy Transformer
Wavy Transformer
Satoshi Noguchi
Yoshinobu Kawahara
118
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0
18 Aug 2025
TANGO: Graph Neural Dynamics via Learned Energy and Tangential Flows
TANGO: Graph Neural Dynamics via Learned Energy and Tangential Flows
Moshe Eliasof
E. Haber
Carola-Bibiane Schönlieb
112
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0
07 Aug 2025
Numerical PDE solvers outperform neural PDE solvers
Numerical PDE solvers outperform neural PDE solvers
Patrick Chatain
Michael Rizvi-Martel
Guillaume Rabusseau
Adam Oberman
AI4CE
129
1
0
28 Jul 2025
ASNN: Learning to Suggest Neural Architectures from Performance Distributions
ASNN: Learning to Suggest Neural Architectures from Performance Distributions
Jinwook Hong
60
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0
27 Jul 2025
Multi-Level Monte Carlo Training of Neural Operators
Multi-Level Monte Carlo Training of Neural Operators
James Rowbottom
Stefania Fresca
Pietro Lio
Carola-Bibiane Schönlieb
Nicolas Boullé
AI4CE
358
2
0
19 May 2025
Optimal Control for Transformer Architectures: Enhancing Generalization, Robustness and Efficiency
Optimal Control for Transformer Architectures: Enhancing Generalization, Robustness and Efficiency
Kelvin Kan
Xingjian Li
Benjamin J. Zhang
Tuhin Sahai
Stanley Osher
Markos A. Katsoulakis
220
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0
16 May 2025
Geometric Fault-Tolerant Neural Network Tracking Control of Unknown Systems on Matrix Lie Groups
Geometric Fault-Tolerant Neural Network Tracking Control of Unknown Systems on Matrix Lie Groups
Robin Chhabra
Farzaneh Abdollahi
279
0
0
07 May 2025
Monotone Peridynamic Neural Operator for Nonlinear Material Modeling with Conditionally Unique Solutions
Monotone Peridynamic Neural Operator for Nonlinear Material Modeling with Conditionally Unique Solutions
Jihong Wang
Xiaochuan Tian
Zhongqiang Zhang
Stewart Silling
S. Jafarzadeh
Yue Yu
329
2
0
02 May 2025
DISCO: learning to DISCover an evolution Operator for multi-physics-agnostic prediction
DISCO: learning to DISCover an evolution Operator for multi-physics-agnostic prediction
Rudy Morel
Jiequn Han
Edouard Oyallon
AI4CE
265
6
0
28 Apr 2025
Flowing Through Layers: A Continuous Dynamical Systems Perspective on Transformers
Flowing Through Layers: A Continuous Dynamical Systems Perspective on Transformers
Jacob Fein-Ashley
AI4CE
333
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0
08 Feb 2025
OT-Transformer: A Continuous-time Transformer Architecture with Optimal Transport Regularization
OT-Transformer: A Continuous-time Transformer Architecture with Optimal Transport Regularization
Kelvin Kan
Xingjian Li
Stanley Osher
427
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0
30 Jan 2025
A Tunable Despeckling Neural Network Stabilized via Diffusion Equation
A Tunable Despeckling Neural Network Stabilized via Diffusion EquationSignal Processing (Signal Process.), 2024
Yi Ran
Zhichang Guo
Jia Li
Yao Li
Martin Burger
Boying Wu
DiffM
275
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0
24 Nov 2024
Predictor-Corrector Enhanced Transformers with Exponential Moving
  Average Coefficient Learning
Predictor-Corrector Enhanced Transformers with Exponential Moving Average Coefficient LearningNeural Information Processing Systems (NeurIPS), 2024
Yangqiu Song
Tong Zheng
Ran Wang
Jiahao Liu
Qingyan Guo
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Tong Xiao
Jingbo Zhu
Jiadong Wang
Xunliang Cai
313
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CAPEEN: Image Captioning with Early Exits and Knowledge Distillation
CAPEEN: Image Captioning with Early Exits and Knowledge DistillationConference on Empirical Methods in Natural Language Processing (EMNLP), 2024
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M. Hanawal
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Invertible ResNets for Inverse Imaging Problems: Competitive Performance with Provable Regularization Properties
Invertible ResNets for Inverse Imaging Problems: Competitive Performance with Provable Regularization Properties
Clemens Arndt
Judith Nickel
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Scale generalisation properties of extended scale-covariant and scale-invariant Gaussian derivative networks on image datasets with spatial scaling variations
Scale generalisation properties of extended scale-covariant and scale-invariant Gaussian derivative networks on image datasets with spatial scaling variationsJournal of Mathematical Imaging and Vision (JMIV), 2024
Andrzej Perzanowski
Tony Lindeberg
425
4
0
17 Sep 2024
Learning Regularization for Graph Inverse Problems
Learning Regularization for Graph Inverse ProblemsAAAI Conference on Artificial Intelligence (AAAI), 2024
Moshe Eliasof
Md Shahriar Rahim Siddiqui
Carola-Bibiane Schönlieb
Eldad Haber
GNN
332
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19 Aug 2024
Operator Learning Using Random Features: A Tool for Scientific Computing
Operator Learning Using Random Features: A Tool for Scientific ComputingSIAM Review (SIAM Rev.), 2024
Nicholas H. Nelsen
Andrew M. Stuart
277
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12 Aug 2024
LIP-CAR: contrast agent reduction by a deep learned inverse problem
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Davide Bianchi
Sonia Colombo Serra
Davide Evangelista
Pengpeng Luo
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Giovanni Valbusa
MedIm
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Fully invertible hyperbolic neural networks for segmenting large-scale
  surface and sub-surface data
Fully invertible hyperbolic neural networks for segmenting large-scale surface and sub-surface data
Bas Peters
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Keegan Lensink
136
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Advection Augmented Convolutional Neural Networks
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N. Zakariaei
Siddharth Rout
Eldad Haber
Moshe Eliasof
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212
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Graph Neural Reaction Diffusion Models
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Eran Treister
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Beyond Conventional Parametric Modeling: Data-Driven Framework for
  Estimation and Prediction of Time Activity Curves in Dynamic PET Imaging
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N. Zakariaei
Arman Rahmim
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Neuroexplicit Diffusion Models for Inpainting of Optical Flow Fields
Neuroexplicit Diffusion Models for Inpainting of Optical Flow FieldsInternational Conference on Machine Learning (ICML), 2024
Tom Fischer
Pascal Peter
Joachim Weickert
Eddy Ilg
DiffMAI4CE
137
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0
23 May 2024
Continuous Learned Primal Dual
Continuous Learned Primal DualInternational Workshop on Machine Learning for Signal Processing (MLSP), 2024
Christina Runkel
A. Biguri
Carola-Bibiane Schönlieb
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142
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Graph Neural Aggregation-diffusion with Metastability
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303
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Neural Fractional Differential Equations
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Equivariant Manifold Neural ODEs and Differential Invariants
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Accelerating Fractional PINNs using Operational Matrices of Derivative
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On The Temporal Domain of Differential Equation Inspired Graph Neural
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284
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Delong Zhang
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  Beyond
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Lequan Lin
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