Partition and Code: learning how to compress graphs

5 July 2021

Papers citing "Partition and Code: learning how to compress graphs"

9 / 9 papers shown

Title
Equivariant Subgraph Aggregation Networks Beatrice Bevilacqua Fabrizio Frasca Derek Lim Balasubramaniam Srinivasan Chen Cai G. Balamurugan M. Bronstein Haggai Maron 22 174 0 06 Oct 2021
Online Graph Dictionary Learning Cédric Vincent-Cuaz Titouan Vayer Rémi Flamary Marco Corneli Nicolas Courty 26 42 0 12 Feb 2021
GraphDF: A Discrete Flow Model for Molecular Graph Generation Youzhi Luo Keqiang Yan Shuiwang Ji DRL 163 185 0 01 Feb 2021
Learning Better Lossless Compression Using Lossy Compression Fabian Mentzer Luc Van Gool Michael Tschannen 64 67 0 23 Mar 2020
COPT: Coordinated Optimal Transport for Graph Sketching Yihe Dong W. Sawin OT 34 26 0 09 Mar 2020
Benchmarking Graph Neural Networks Vijay Prakash Dwivedi Chaitanya K. Joshi Anh Tuan Luu T. Laurent Yoshua Bengio Xavier Bresson 181 907 0 02 Mar 2020
Junction Tree Variational Autoencoder for Molecular Graph Generation Wengong Jin Regina Barzilay Tommi Jaakkola 211 1,329 0 12 Feb 2018
Pixel Recurrent Neural Networks Aaron van den Oord Nal Kalchbrenner Koray Kavukcuoglu SSeg GAN 225 2,542 0 25 Jan 2016
Parsimonious module inference in large networks Tiago P. Peixoto MoE 40 200 0 19 Dec 2012