PGM-Explainer: Probabilistic Graphical Model Explanations for Graph Neural Networks

12 October 2020

Papers citing "PGM-Explainer: Probabilistic Graphical Model Explanations for Graph Neural Networks"

28 / 28 papers shown

Title
Towards Comprehensive and Prerequisite-Free Explainer for Graph Neural Networks Han Zhang Yan Wang Guanfeng Liu Pengfei Ding Huaxiong Wang Kwok-Yan Lam 80 0 0 20 May 2025
MAGE: Model-Level Graph Neural Networks Explanations via Motif-based Graph Generation Zhaoning Yu Hongyang Gao 109 3 0 21 May 2024
PyTorch: An Imperative Style, High-Performance Deep Learning Library Adam Paszke Sam Gross Francisco Massa Adam Lerer James Bradbury ... Sasank Chilamkurthy Benoit Steiner Lu Fang Junjie Bai Soumith Chintala ODL 520 42,449 0 03 Dec 2019
Deep Graph Library: A Graph-Centric, Highly-Performant Package for Graph Neural Networks Minjie Wang Da Zheng Zihao Ye Quan Gan Mufei Li ... Jiaqi Zhao Haotong Zhang Alex Smola Jinyang Li Zheng Zhang AI4CE GNN 286 757 0 03 Sep 2019
c-Eval: A Unified Metric to Evaluate Feature-based Explanations via Perturbation Minh Nhat Vu Truc D. T. Nguyen Nhathai Phan Ralucca Gera My T. Thai AAML FAtt 41 22 0 05 Jun 2019
Self-Attention Graph Pooling Junhyun Lee Inyeop Lee Jaewoo Kang GNN 175 1,121 0 17 Apr 2019
GNNExplainer: Generating Explanations for Graph Neural Networks Rex Ying Dylan Bourgeois Jiaxuan You Marinka Zitnik J. Leskovec LLMAG 150 1,323 0 10 Mar 2019
How Powerful are Graph Neural Networks? Keyulu Xu Weihua Hu J. Leskovec Stefanie Jegelka GNN 243 7,653 0 01 Oct 2018
Hierarchical Graph Representation Learning with Differentiable Pooling Rex Ying Jiaxuan You Christopher Morris Xiang Ren William L. Hamilton J. Leskovec GNN 297 2,148 0 22 Jun 2018
Graph Convolutional Policy Network for Goal-Directed Molecular Graph Generation Jiaxuan You Bowen Liu Rex Ying Vijay S. Pande J. Leskovec GNN 293 902 0 07 Jun 2018
Link Prediction Based on Graph Neural Networks Muhan Zhang Yixin Chen GNN 98 1,937 0 27 Feb 2018
MotifNet: a motif-based Graph Convolutional Network for directed graphs Federico Monti Karl Otness M. Bronstein GNN 75 144 0 04 Feb 2018
Modeling polypharmacy side effects with graph convolutional networks Marinka Zitnik Monica Agrawal J. Leskovec GNN 116 1,083 0 02 Feb 2018
Graph Attention Networks Petar Velickovic Guillem Cucurull Arantxa Casanova Adriana Romero Pietro Lio Yoshua Bengio GNN 479 20,164 0 30 Oct 2017
Inductive Representation Learning on Large Graphs William L. Hamilton Z. Ying J. Leskovec 509 15,247 0 07 Jun 2017
A Unified Approach to Interpreting Model Predictions Scott M. Lundberg Su-In Lee FAtt 1.1K 21,939 0 22 May 2017
CayleyNets: Graph Convolutional Neural Networks with Complex Rational Spectral Filters Ron Levie Federico Monti Xavier Bresson M. Bronstein GNN 185 659 0 22 May 2017
Learning Important Features Through Propagating Activation Differences Avanti Shrikumar Peyton Greenside A. Kundaje FAtt 201 3,873 0 10 Apr 2017
Towards A Rigorous Science of Interpretable Machine Learning Finale Doshi-Velez Been Kim XAI FaML 402 3,798 0 28 Feb 2017
Gradients of Counterfactuals Mukund Sundararajan Ankur Taly Qiqi Yan FAtt 56 104 0 08 Nov 2016
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization Ramprasaath R. Selvaraju Michael Cogswell Abhishek Das Ramakrishna Vedantam Devi Parikh Dhruv Batra FAtt 318 20,023 0 07 Oct 2016
Semi-Supervised Classification with Graph Convolutional Networks Thomas Kipf Max Welling GNN SSL 644 29,076 0 09 Sep 2016
Top-down Neural Attention by Excitation Backprop Jianming Zhang Zhe Lin Jonathan Brandt Xiaohui Shen Stan Sclaroff 81 947 0 01 Aug 2016
Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering M. Defferrard Xavier Bresson P. Vandergheynst GNN 350 7,655 0 30 Jun 2016
"Why Should I Trust You?": Explaining the Predictions of Any Classifier Marco Tulio Ribeiro Sameer Singh Carlos Guestrin FAtt FaML 1.2K 16,990 0 16 Feb 2016
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 1.9K 150,115 0 22 Dec 2014
Striving for Simplicity: The All Convolutional Net Jost Tobias Springenberg Alexey Dosovitskiy Thomas Brox Martin Riedmiller FAtt 248 4,672 0 21 Dec 2014
Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps Karen Simonyan Andrea Vedaldi Andrew Zisserman FAtt 312 7,308 0 20 Dec 2013