PyTorch Geometric Signed Directed: A Software Package on Graph Neural Networks for Signed and Directed Graphs

22 February 2022

Papers citing "PyTorch Geometric Signed Directed: A Software Package on Graph Neural Networks for Signed and Directed Graphs"

9 / 9 papers shown

Title
Toward Data-centric Directed Graph Learning: An Entropy-driven Approach Xunkai Li Zhengyu Wu Kaichi Yu Hongchao Qin Guang Zeng Rong-Hua Li Guoren Wang 35 0 0 02 May 2025
Understanding the Design Principles of Link Prediction in Directed Settings Jun Zhai Muberra Ozmen Thomas Markovich AI4CE 33 0 0 24 Feb 2025
A Benchmark on Directed Graph Representation Learning in Hardware Designs Haoyu Wang Yinan Huang Nan Wu Pan Li OOD 38 1 0 09 Oct 2024
Graph Learning in 4D: a Quaternion-valued Laplacian to Enhance Spectral GCNs Stefano Fiorini Stefano Coniglio Michele Ciavotta Enza Messina GNN 24 5 0 28 Dec 2023
Edge Directionality Improves Learning on Heterophilic Graphs Emanuele Rossi Bertrand Charpentier Francesco Di Giovanni Fabrizio Frasca Stephan Günnemann Michael M. Bronstein 15 56 0 17 May 2023
GNNRank: Learning Global Rankings from Pairwise Comparisons via Directed Graph Neural Networks Yixuan He Quan Gan David Wipf G. Reinert Junchi Yan Mihai Cucuringu GNN FedML 18 19 0 01 Feb 2022
SDGNN: Learning Node Representation for Signed Directed Networks Junjie Huang Huawei Shen Liang Hou Xueqi Cheng 29 83 0 07 Jan 2021
Geom-GCN: Geometric Graph Convolutional Networks Hongbin Pei Bingzhen Wei Kevin Chen-Chuan Chang Yu Lei Bo Yang GNN 169 1,077 0 13 Feb 2020
Multi-scale Attributed Node Embedding Benedek Rozemberczki Carl Allen Rik Sarkar GNN 145 833 0 28 Sep 2019