Partition and Code: learning how to compress graphs

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Partition and Code: learning how to compress graphs

5 July 2021

Giorgos Bouritsas

Nikolaos Karalias

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

8 / 8 papers shown

Title
GALA: Geometry-Aware Local Adaptive Grids for Detailed 3D Generation Dingdong Yang Yizhi Wang Konrad Schindler Ali Mahdavi Amiri Hao Zhang 87 1 0 13 Oct 2024
Graph Generation with $K^2$ -trees Yunhui Jang Dongwoo Kim SungSoo Ahn 130 2 0 30 May 2023
Random Edge Coding: One-Shot Bits-Back Coding of Large Labeled Graphs Daniel de Souza Severo James Townsend Ashish Khisti Alireza Makhzani 58 2 0 16 May 2023
Graph Summarization via Node Grouping: A Spectral Algorithm Arpit Merchant M. Mathioudakis Yanhao Wang 35 3 0 08 Nov 2022
Graph-in-Graph (GiG): Learning interpretable latent graphs in non-Euclidean domain for biological and healthcare applications Kamilia Mullakaeva Luca Cosmo Anees Kazi Seyed-Ahmad Ahmadi Nassir Navab Michael M. Bronstein 83 8 0 01 Apr 2022
Graph Kernel Neural Networks Luca Cosmo G. Minello Alessandro Bicciato M. Bronstein Emanuele Rodolà Luca Rossi A. Torsello GNN 70 22 0 14 Dec 2021
Equivariant Subgraph Aggregation Networks Beatrice Bevilacqua Fabrizio Frasca Derek Lim Balasubramaniam Srinivasan Chen Cai G. Balamurugan M. Bronstein Haggai Maron 130 180 0 06 Oct 2021
Benchmarking Graph Neural Networks Vijay Prakash Dwivedi Chaitanya K. Joshi Anh Tuan Luu T. Laurent Yoshua Bengio Xavier Bresson 607 955 0 02 Mar 2020

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