Universal approximations of invariant maps by neural networks

26 April 2018

Papers citing "Universal approximations of invariant maps by neural networks"

34 / 134 papers shown

Title
Expressivity of Deep Neural Networks Ingo Gühring Mones Raslan Gitta Kutyniok 16 50 0 09 Jul 2020
MDP Homomorphic Networks: Group Symmetries in Reinforcement Learning Elise van der Pol Daniel E. Worrall H. V. Hoof F. Oliehoek Max Welling BDL AI4CE 31 155 0 30 Jun 2020
Expressive Power of Invariant and Equivariant Graph Neural Networks Waïss Azizian Marc Lelarge 25 111 0 28 Jun 2020
Lorentz Group Equivariant Neural Network for Particle Physics A. Bogatskiy Brandon M. Anderson Jan T. Offermann M. Roussi David W. Miller Risi Kondor AI4CE 29 136 0 08 Jun 2020
Structure preserving deep learning E. Celledoni Matthias Joachim Ehrhardt Christian Etmann R. McLachlan B. Owren Carola-Bibiane Schönlieb Ferdia Sherry AI4CE 15 43 0 05 Jun 2020
The general theory of permutation equivarant neural networks and higher order graph variational encoders Erik H. Thiede Truong Son-Hy Risi Kondor 24 35 0 08 Apr 2020
On the rate of convergence of image classifiers based on convolutional neural networks Michael Kohler A. Krzyżak Benjamin Walter 17 16 0 03 Mar 2020
Overall error analysis for the training of deep neural networks via stochastic gradient descent with random initialisation Arnulf Jentzen Timo Welti 9 15 0 03 Mar 2020
Set2Graph: Learning Graphs From Sets Hadar Serviansky Nimrod Segol Jonathan Shlomi Kyle Cranmer Eilam Gross Haggai Maron Y. Lipman PINN GNN 14 35 0 20 Feb 2020
On Learning Sets of Symmetric Elements Haggai Maron Or Litany Gal Chechik Ethan Fetaya 30 132 0 20 Feb 2020
A Computationally Efficient Neural Network Invariant to the Action of Symmetry Subgroups Piotr Kicki Mete Ozay Piotr Skrzypczyñski 4 4 0 18 Feb 2020
Universal Equivariant Multilayer Perceptrons Siamak Ravanbakhsh 98 48 0 07 Feb 2020
Improved Generalization Bounds of Group Invariant / Equivariant Deep Networks via Quotient Feature Spaces Akiyoshi Sannai Masaaki Imaizumi M. Kawano MLT 20 29 0 15 Oct 2019
A Simple Proof of the Universality of Invariant/Equivariant Graph Neural Networks Takanori Maehara Hoang NT 19 29 0 09 Oct 2019
On Universal Equivariant Set Networks Nimrod Segol Y. Lipman 3DPC 17 63 0 06 Oct 2019
Full error analysis for the training of deep neural networks C. Beck Arnulf Jentzen Benno Kuckuck 14 47 0 30 Sep 2019
PINE: Universal Deep Embedding for Graph Nodes via Partial Permutation Invariant Set Functions Shupeng Gui Xiangliang Zhang Pan Zhong Shuang Qiu Mingrui Wu Jieping Ye Zhengdao Wang Ji Liu 19 15 0 25 Sep 2019
Solving Continual Combinatorial Selection via Deep Reinforcement Learning Hyungseok Song Hyeryung Jang H. Tran Se-eun Yoon Kyunghwan Son Donggyu Yun Hyoju Chung Yung Yi 10 10 0 09 Sep 2019
Learning Set-equivariant Functions with SWARM Mappings Roland Vollgraf 13 3 0 22 Jun 2019
Neural Networks on Groups Stella Biderman 28 1 0 13 Jun 2019
On the equivalence between graph isomorphism testing and function approximation with GNNs Zhengdao Chen Soledad Villar Lei Chen Joan Bruna 20 275 0 29 May 2019
Graph Neural Networks Exponentially Lose Expressive Power for Node Classification Kenta Oono Taiji Suzuki GNN 32 27 0 27 May 2019
Universal Invariant and Equivariant Graph Neural Networks Nicolas Keriven Gabriel Peyré 22 287 0 13 May 2019
HARK Side of Deep Learning -- From Grad Student Descent to Automated Machine Learning O. Gencoglu M. Gils E. Guldogan Chamin Morikawa Mehmet Süzen M. Gruber J. Leinonen H. Huttunen 11 36 0 16 Apr 2019
Approximation and Non-parametric Estimation of ResNet-type Convolutional Neural Networks Kenta Oono Taiji Suzuki 27 58 0 24 Mar 2019
Universal approximations of permutation invariant/equivariant functions by deep neural networks Akiyoshi Sannai Yuuki Takai Matthieu Cordonnier 21 67 0 05 Mar 2019
An Algorithm for Approximating Continuous Functions on Compact Subsets with a Neural Network with one Hidden Layer Elliott Zaresky-Williams MLT 13 1 0 10 Feb 2019
On the Universality of Invariant Networks Haggai Maron Ethan Fetaya Nimrod Segol Y. Lipman OOD 6 236 0 27 Jan 2019
Invariant and Equivariant Graph Networks Haggai Maron Heli Ben-Hamu Nadav Shamir Y. Lipman 20 494 0 24 Dec 2018
A proof that deep artificial neural networks overcome the curse of dimensionality in the numerical approximation of Kolmogorov partial differential equations with constant diffusion and nonlinear drift coefficients Arnulf Jentzen Diyora Salimova Timo Welti AI4CE 16 116 0 19 Sep 2018
Analysis of the Generalization Error: Empirical Risk Minimization over Deep Artificial Neural Networks Overcomes the Curse of Dimensionality in the Numerical Approximation of Black-Scholes Partial Differential Equations Julius Berner Philipp Grohs Arnulf Jentzen 4 181 0 09 Sep 2018
A proof that artificial neural networks overcome the curse of dimensionality in the numerical approximation of Black-Scholes partial differential equations Philipp Grohs F. Hornung Arnulf Jentzen Philippe von Wurstemberger 9 167 0 07 Sep 2018
Equivalence of approximation by convolutional neural networks and fully-connected networks P. Petersen Felix Voigtländer 12 78 0 04 Sep 2018
Optimal Approximation with Sparsely Connected Deep Neural Networks Helmut Bölcskei Philipp Grohs Gitta Kutyniok P. Petersen 19 255 0 04 May 2017