Invariant and Equivariant Graph Networks

24 December 2018

Papers citing "Invariant and Equivariant Graph Networks"

24 / 124 papers shown

Title
Distance Encoding: Design Provably More Powerful Neural Networks for Graph Representation Learning Pan Li Yanbang Wang Hongwei Wang J. Leskovec GNN 20 12 0 31 Aug 2020
Expressive Power of Invariant and Equivariant Graph Neural Networks Waïss Azizian Marc Lelarge 22 111 0 28 Jun 2020
Improving Graph Neural Network Expressivity via Subgraph Isomorphism Counting Giorgos Bouritsas Fabrizio Frasca S. Zafeiriou M. Bronstein 46 423 0 16 Jun 2020
Global Attention Improves Graph Networks Generalization Omri Puny Heli Ben-Hamu Y. Lipman 27 22 0 14 Jun 2020
The Convolution Exponential and Generalized Sylvester Flows Emiel Hoogeboom Victor Garcia Satorras Jakub M. Tomczak Max Welling 17 28 0 02 Jun 2020
Symmetry & critical points for a model shallow neural network Yossi Arjevani M. Field 26 13 0 23 Mar 2020
On Learning Sets of Symmetric Elements Haggai Maron Or Litany Gal Chechik Ethan Fetaya 22 132 0 20 Feb 2020
Can Graph Neural Networks Count Substructures? Zhengdao Chen Lei Chen Soledad Villar Joan Bruna GNN 54 319 0 10 Feb 2020
Random Features Strengthen Graph Neural Networks Ryoma Sato M. Yamada H. Kashima GNN AAML 13 230 0 08 Feb 2020
Universal Equivariant Multilayer Perceptrons Siamak Ravanbakhsh 98 48 0 07 Feb 2020
Representation Learning on Unit Ball with 3D Roto-Translational Equivariance Sameera Ramasinghe Salman Khan Nick Barnes Stephen Gould 13 8 0 30 Nov 2019
A Simple Proof of the Universality of Invariant/Equivariant Graph Neural Networks Takanori Maehara Hoang NT 19 29 0 09 Oct 2019
On the Equivalence between Positional Node Embeddings and Structural Graph Representations Balasubramaniam Srinivasan Bruno Ribeiro 17 27 0 01 Oct 2019
Universal Graph Transformer Self-Attention Networks D. Q. Nguyen T. Nguyen Dinh Q. Phung ViT 28 63 0 26 Sep 2019
Graph Random Neural Features for Distance-Preserving Graph Representations Daniele Zambon C. Alippi L. Livi 16 1 0 09 Sep 2019
Transferability of Spectral Graph Convolutional Neural Networks Ron Levie Wei Huang Lorenzo Bucci M. Bronstein Gitta Kutyniok GNN 27 125 0 30 Jul 2019
Incidence Networks for Geometric Deep Learning Marjan Albooyeh Daniele Bertolini Siamak Ravanbakhsh GNN 17 26 0 27 May 2019
Provably Powerful Graph Networks Haggai Maron Heli Ben-Hamu Hadar Serviansky Y. Lipman 22 562 0 27 May 2019
Relational Pooling for Graph Representations R. Murphy Balasubramaniam Srinivasan Vinayak A. Rao Bruno Ribeiro GNN 24 255 0 06 Mar 2019
Gauge Equivariant Convolutional Networks and the Icosahedral CNN Taco S. Cohen Maurice Weiler Berkay Kicanaoglu Max Welling 38 402 0 11 Feb 2019
A Comprehensive Survey on Graph Neural Networks Zonghan Wu Shirui Pan Fengwen Chen Guodong Long Chengqi Zhang Philip S. Yu FaML GNN AI4TS AI4CE 153 8,350 0 03 Jan 2019
Graph Neural Networks: A Review of Methods and Applications Jie Zhou Ganqu Cui Shengding Hu Zhengyan Zhang Cheng Yang Zhiyuan Liu Lifeng Wang Changcheng Li Maosong Sun AI4CE GNN 28 5,397 0 20 Dec 2018
A General Theory of Equivariant CNNs on Homogeneous Spaces Taco S. Cohen Mario Geiger Maurice Weiler MLT AI4CE 156 308 0 05 Nov 2018
Geometric deep learning on graphs and manifolds using mixture model CNNs Federico Monti Davide Boscaini Jonathan Masci Emanuele Rodolà Jan Svoboda M. Bronstein GNN 251 1,811 0 25 Nov 2016