Towards characterizing the value of edge embeddings in Graph Neural Networks

13 October 2024

Papers citing "Towards characterizing the value of edge embeddings in Graph Neural Networks"

10 / 10 papers shown

Title
Transformers, parallel computation, and logarithmic depth Clayton Sanford Daniel J. Hsu Matus Telgarsky 61 38 0 14 Feb 2024
A Short Tutorial on The Weisfeiler-Lehman Test And Its Variants Ningyuan Huang Soledad Villar 52 63 0 18 Jan 2022
Line Graph Neural Networks for Link Prediction Lei Cai Jundong Li Jie Wang Shuiwang Ji GNN 201 200 0 20 Oct 2020
Benchmarking Graph Neural Networks Vijay Prakash Dwivedi Chaitanya K. Joshi Anh Tuan Luu T. Laurent Yoshua Bengio Xavier Bresson 438 940 0 02 Mar 2020
What graph neural networks cannot learn: depth vs width Andreas Loukas GNN 84 299 0 06 Jul 2019
Provably Powerful Graph Networks Haggai Maron Heli Ben-Hamu Hadar Serviansky Y. Lipman 120 579 0 27 May 2019
How Powerful are Graph Neural Networks? Keyulu Xu Weihua Hu J. Leskovec Stefanie Jegelka GNN 243 7,653 0 01 Oct 2018
Neural Message Passing for Quantum Chemistry Justin Gilmer S. Schoenholz Patrick F. Riley Oriol Vinyals George E. Dahl 593 7,455 0 04 Apr 2017
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 543 1,410 0 01 Dec 2016
Semi-Supervised Classification with Graph Convolutional Networks Thomas Kipf Max Welling GNN SSL 644 29,076 0 09 Sep 2016