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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
Continuous-in-Depth Neural Networks A. Queiruga N. Benjamin Erichson D. Taylor Michael W. Mahoney 109 48 0 05 Aug 2020
Wasserstein-based Projections with Applications to Inverse Problems Howard Heaton Samy Wu Fung A. Lin Stanley Osher W. Yin 58 3 0 05 Aug 2020
flexgrid2vec: Learning Efficient Visual Representations Vectors Ali Hamdi D. Kim Flora D. Salim SSL GNN 88 7 0 30 Jul 2020
ResNet After All? Neural ODEs and Their Numerical Solution Katharina Ott P. Katiyar Philipp Hennig Michael Tiemann 88 31 0 30 Jul 2020
Train Like a (Var)Pro: Efficient Training of Neural Networks with Variable Projection Elizabeth Newman Lars Ruthotto Joseph L. Hart B. V. B. Waanders AAML 125 19 0 26 Jul 2020
PDO-eConvs: Partial Differential Operator Based Equivariant Convolutions Zhengyang Shen Lingshen He Zhouchen Lin Jinwen Ma 97 47 0 20 Jul 2020
Learning Differential Equations that are Easy to Solve Jacob Kelly J. Bettencourt Matthew J. Johnson David Duvenaud 113 117 0 09 Jul 2020
Lipschitz Recurrent Neural Networks N. Benjamin Erichson Omri Azencot A. Queiruga Liam Hodgkinson Michael W. Mahoney 90 112 0 22 Jun 2020
STEER: Simple Temporal Regularization For Neural ODEs Arna Ghosh Harkirat Singh Behl Emilien Dupont Philip Torr Vinay P. Namboodiri BDL AI4TS 104 75 0 18 Jun 2020
A Shooting Formulation of Deep Learning François-Xavier Vialard Roland Kwitt Susan Wei Marc Niethammer 47 13 0 18 Jun 2020
Go with the Flow: Adaptive Control for Neural ODEs Mathieu Chalvidal Matthew Ricci Rufin VanRullen Thomas Serre 43 2 0 16 Jun 2020
Learning continuous-time PDEs from sparse data with graph neural networks V. Iakovlev Markus Heinonen Harri Lähdesmäki AI4CE 86 70 0 16 Jun 2020
On Second Order Behaviour in Augmented Neural ODEs Alexander Norcliffe Cristian Bodnar Ben Day Nikola Simidjievski Pietro Lio 85 94 0 12 Jun 2020
Learning normalizing flows from Entropy-Kantorovich potentials Chris Finlay Augusto Gerolin Adam M. Oberman Aram-Alexandre Pooladian 99 24 0 10 Jun 2020
DiffGCN: Graph Convolutional Networks via Differential Operators and Algebraic Multigrid Pooling Moshe Eliasof Eran Treister 65 25 0 07 Jun 2020
Structure preserving deep learning E. Celledoni Matthias Joachim Ehrhardt Christian Etmann R. McLachlan B. Owren Carola-Bibiane Schönlieb Ferdia Sherry AI4CE 119 44 0 05 Jun 2020
Adaptive Checkpoint Adjoint Method for Gradient Estimation in Neural ODE Juntang Zhuang Nicha Dvornek Xiaoxiao Li S. Tatikonda X. Papademetris James Duncan BDL 119 112 0 03 Jun 2020
Continuous-time system identification with neural networks: Model structures and fitting criteria Marco Forgione Dario Piga 74 66 0 03 Jun 2020
Temporal-Differential Learning in Continuous Environments T. Bian Zhong-Ping Jiang CLL OffRL 13 1 0 01 Jun 2020
Discretize-Optimize vs. Optimize-Discretize for Time-Series Regression and Continuous Normalizing Flows Derek Onken Lars Ruthotto BDL 75 54 0 27 May 2020
Fourier Neural Networks as Function Approximators and Differential Equation Solvers M. Ngom O. Marin 49 2 0 27 May 2020
The Random Feature Model for Input-Output Maps between Banach Spaces Nicholas H. Nelsen Andrew M. Stuart 93 144 0 20 May 2020
Model Reduction and Neural Networks for Parametric PDEs K. Bhattacharya Bamdad Hosseini Nikola B. Kovachki Andrew M. Stuart 245 334 0 07 May 2020
Neural Differential Equations for Single Image Super-resolution Teven Le Scao 47 2 0 02 May 2020
Fractional Deep Neural Network via Constrained Optimization Harbir Antil R. Khatri R. Löhner Deepanshu Verma 60 29 0 01 Apr 2020
Deep connections between learning from limited labels & physical parameter estimation -- inspiration for regularization Bas Peters AI4CE 38 0 0 17 Mar 2020
Interpolation Technique to Speed Up Gradients Propagation in Neural ODEs Talgat Daulbaev A. Katrutsa L. Markeeva Julia Gusak A. Cichocki Ivan Oseledets 69 8 0 11 Mar 2020
Integrating Scientific Knowledge with Machine Learning for Engineering and Environmental Systems J. Willard X. Jia Shaoming Xu M. Steinbach Vipin Kumar AI4CE 156 414 0 10 Mar 2020
Alternating the Population and Control Neural Networks to Solve High-Dimensional Stochastic Mean-Field Games A. Lin Samy Wu Fung Wuchen Li L. Nurbekyan Stanley J. Osher 92 74 0 24 Feb 2020
Stochastic Runge-Kutta methods and adaptive SGD-G2 stochastic gradient descent I. Ayadi Gabriel Turinici ODL 35 9 0 20 Feb 2020
How to train your neural ODE: the world of Jacobian and kinetic regularization Chris Finlay J. Jacobsen L. Nurbekyan Adam M. Oberman 73 302 0 07 Feb 2020
Translating Diffusion, Wavelets, and Regularisation into Residual Networks Tobias Alt Joachim Weickert Pascal Peter DiffM 52 8 0 07 Feb 2020
PDE-NetGen 1.0: from symbolic PDE representations of physical processes to trainable neural network representations O. Pannekoucke Ronan Fablet AI4CE PINN DiffM 38 8 0 03 Feb 2020
AdvectiveNet: An Eulerian-Lagrangian Fluidic reservoir for Point Cloud Processing Xingzhe He Helen Lu Cao Bo Zhu 3DPC 35 9 0 01 Feb 2020
PDE-based Group Equivariant Convolutional Neural Networks B. Smets J. Portegies Erik J. Bekkers R. Duits AI4CE 102 54 0 24 Jan 2020
SympNets: Intrinsic structure-preserving symplectic networks for identifying Hamiltonian systems Pengzhan Jin Zhen Zhang Aiqing Zhu Yifa Tang George Karniadakis 105 21 0 11 Jan 2020
Mean-Field and Kinetic Descriptions of Neural Differential Equations Michael Herty T. Trimborn G. Visconti 118 6 0 07 Jan 2020
ODE-based Deep Network for MRI Reconstruction A. Yazdanpanah O. Afacan Simon K. Warfield OOD 38 3 0 27 Dec 2019
Deep Learning via Dynamical Systems: An Approximation Perspective Qianxiao Li Ting Lin Zuowei Shen AI4TS AI4CE 101 109 0 22 Dec 2019
Multilevel Initialization for Layer-Parallel Deep Neural Network Training E. Cyr Stefanie Günther J. Schroder AI4CE 54 11 0 19 Dec 2019
Symmetric block-low-rank layers for fully reversible multilevel neural networks Bas Peters E. Haber Keegan Lensink 20 6 0 14 Dec 2019
Dynamical System Inspired Adaptive Time Stepping Controller for Residual Network Families Yibo Yang Jianlong Wu Hongyang Li Xia Li Tiancheng Shen Zhouchen Lin OOD 73 21 0 23 Nov 2019
Discrete and Continuous Deep Residual Learning Over Graphs Pedro H. C. Avelar Anderson R. Tavares Marco Gori Luís C. Lamb GNN 65 20 0 21 Nov 2019
Review: Ordinary Differential Equations For Deep Learning Xinshi Chen AI4TS AI4CE 55 5 0 01 Nov 2019
LeanConvNets: Low-cost Yet Effective Convolutional Neural Networks Jonathan Ephrath Moshe Eliasof Lars Ruthotto E. Haber Eran Treister 131 17 0 29 Oct 2019
Neural Similarity Learning Weiyang Liu Zhen Liu James M. Rehg Le Song 94 30 0 28 Oct 2019
Neural network augmented wave-equation simulation Ali Siahkoohi M. Louboutin Felix J. Herrmann 39 15 0 27 Sep 2019
Differential equations as models of deep neural networks J. Ruseckas 21 3 0 09 Sep 2019
Port-Hamiltonian Approach to Neural Network Training Stefano Massaroli Michael Poli Federico Califano Angela Faragasso Jinkyoo Park Atsushi Yamashita Hajime Asama 55 14 0 06 Sep 2019
An Event-Driven Approach to Serverless Seismic Imaging in the Cloud Philipp A. Witte M. Louboutin H. Modzelewski Charles Jones J. Selvage Felix J. Herrmann 38 21 0 03 Sep 2019