Universal Invariant and Equivariant Graph Neural Networks

13 May 2019

Papers citing "Universal Invariant and Equivariant Graph Neural Networks"

26 / 76 papers shown

Title
Graph Neural Networks with Local Graph Parameters Pablo Barceló Floris Geerts Juan L. Reutter Maksimilian Ryschkov 24 64 0 12 Jun 2021
Scalars are universal: Equivariant machine learning, structured like classical physics Soledad Villar D. Hogg Kate Storey-Fisher Weichi Yao Ben Blum-Smith PINN AI4CE 24 130 0 11 Jun 2021
Breaking the Limits of Message Passing Graph Neural Networks M. Balcilar Pierre Héroux Benoit Gaüzère Pascal Vasseur Sébastien Adam P. Honeine 15 121 0 08 Jun 2021
Graph Neural Networks: Taxonomy, Advances and Trends Yu Zhou Haixia Zheng Xin Huang Shufeng Hao Dengao Li Jumin Zhao AI4TS 25 115 0 16 Dec 2020
On the Universality of Rotation Equivariant Point Cloud Networks Nadav Dym Haggai Maron 3DPC 27 78 0 06 Oct 2020
GraphNorm: A Principled Approach to Accelerating Graph Neural Network Training Tianle Cai Shengjie Luo Keyulu Xu Di He Tie-Yan Liu Liwei Wang GNN 21 158 0 07 Sep 2020
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 46 424 0 16 Jun 2020
How hard is to distinguish graphs with graph neural networks? Andreas Loukas GNN 25 6 0 13 May 2020
On Learning Sets of Symmetric Elements Haggai Maron Or Litany Gal Chechik Ethan Fetaya 28 132 0 20 Feb 2020
Generalization and Representational Limits of Graph Neural Networks Vikas K. Garg Stefanie Jegelka Tommi Jaakkola GNN 26 303 0 14 Feb 2020
Can Graph Neural Networks Count Substructures? Zhengdao Chen Lei Chen Soledad Villar Joan Bruna GNN 57 319 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
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
Graph Random Neural Features for Distance-Preserving Graph Representations Daniele Zambon C. Alippi L. Livi 16 1 0 09 Sep 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
Solving NP-Hard Problems on Graphs with Extended AlphaGo Zero Kenshi Abe Zijian Xu Issei Sato Masashi Sugiyama GNN AI4CE 27 54 0 28 May 2019
Incidence Networks for Geometric Deep Learning Marjan Albooyeh Daniele Bertolini Siamak Ravanbakhsh GNN 20 26 0 27 May 2019
Provably Powerful Graph Networks Haggai Maron Heli Ben-Hamu Hadar Serviansky Y. Lipman 22 562 0 27 May 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 5,396 0 20 Dec 2018
A General Theory of Equivariant CNNs on Homogeneous Spaces Taco S. Cohen Mario Geiger Maurice Weiler MLT AI4CE 162 308 0 05 Nov 2018
Interaction Networks for Learning about Objects, Relations and Physics Peter W. Battaglia Razvan Pascanu Matthew Lai Danilo Jimenez Rezende Koray Kavukcuoglu AI4CE OCL PINN GNN 278 1,400 0 01 Dec 2016
Geometric deep learning: going beyond Euclidean data M. Bronstein Joan Bruna Yann LeCun Arthur Szlam P. Vandergheynst GNN 250 3,236 0 24 Nov 2016