Distill n' Explain: explaining graph neural networks using simple surrogates

17 March 2023

Papers citing "Distill n' Explain: explaining graph neural networks using simple surrogates"

27 / 27 papers shown

Title
DEGREE: Decomposition Based Explanation For Graph Neural Networks Qizhang Feng Ninghao Liu Fan Yang Ruixiang Tang Mengnan Du Xia Hu 84 23 0 22 May 2023
Which Explanation Should I Choose? A Function Approximation Perspective to Characterizing Post Hoc Explanations Tessa Han Suraj Srinivas Himabindu Lakkaraju FAtt 78 86 0 02 Jun 2022
Dataset Distillation using Neural Feature Regression Yongchao Zhou E. Nezhadarya Jimmy Ba DD FedML 71 157 0 01 Jun 2022
ETA Prediction with Graph Neural Networks in Google Maps Austin Derrow-Pinion Jennifer She David Wong O. Lange Todd Hester ... Ang Li Zhongwen Xu Alvaro Sanchez-Gonzalez Yujia Li Petar Velivcković AI4TS 56 228 0 25 Aug 2021
Probing GNN Explainers: A Rigorous Theoretical and Empirical Analysis of GNN Explanation Methods Chirag Agarwal Marinka Zitnik Himabindu Lakkaraju 48 52 0 16 Jun 2021
Scaling Ensemble Distribution Distillation to Many Classes with Proxy Targets Max Ryabinin A. Malinin Mark Gales UQCV 44 18 0 14 May 2021
Generative Causal Explanations for Graph Neural Networks Wanyu Lin Hao Lan Baochun Li CML 59 176 0 14 Apr 2021
On Explainability of Graph Neural Networks via Subgraph Explorations Hao Yuan Haiyang Yu Jie Wang Kang Li Shuiwang Ji FAtt 78 390 0 09 Feb 2021
CF-GNNExplainer: Counterfactual Explanations for Graph Neural Networks Ana Lucic Maartje ter Hoeve Gabriele Tolomei Maarten de Rijke Fabrizio Silvestri 143 145 0 05 Feb 2021
Cross-Layer Distillation with Semantic Calibration Defang Chen Jian-Ping Mei Yuan Zhang Can Wang Yan Feng Chun-Yen Chen FedML 73 298 0 06 Dec 2020
PLOP: Learning without Forgetting for Continual Semantic Segmentation Arthur Douillard Yifu Chen Arnaud Dapogny Matthieu Cord CLL 44 240 0 23 Nov 2020
Combining Label Propagation and Simple Models Out-performs Graph Neural Networks Qian Huang Horace He Abhay Singh Ser-Nam Lim Austin R. Benson 77 283 0 27 Oct 2020
Reliable Post hoc Explanations: Modeling Uncertainty in Explainability Dylan Slack Sophie Hilgard Sameer Singh Himabindu Lakkaraju FAtt 54 162 0 11 Aug 2020
Simple and Deep Graph Convolutional Networks Ming Chen Zhewei Wei Zengfeng Huang Bolin Ding Yaliang Li GNN 116 1,485 0 04 Jul 2020
Drug discovery with explainable artificial intelligence José Jiménez-Luna F. Grisoni G. Schneider 172 634 0 01 Jul 2020
XGNN: Towards Model-Level Explanations of Graph Neural Networks Haonan Yuan Jiliang Tang Xia Hu Shuiwang Ji 75 398 0 03 Jun 2020
Generalized Bayesian Posterior Expectation Distillation for Deep Neural Networks Meet P. Vadera B. Jalaeian Benjamin M. Marlin BDL FedML UQCV 45 20 0 16 May 2020
SIGN: Scalable Inception Graph Neural Networks Fabrizio Frasca Emanuele Rossi D. Eynard B. Chamberlain M. Bronstein Federico Monti GNN 117 396 0 23 Apr 2020
Distilling Knowledge from Graph Convolutional Networks Yiding Yang Jiayan Qiu Xiuming Zhang Dacheng Tao Xinchao Wang 210 230 0 23 Mar 2020
Learning to Simulate Complex Physics with Graph Networks Alvaro Sanchez-Gonzalez Jonathan Godwin Tobias Pfaff Rex Ying J. Leskovec Peter W. Battaglia PINN AI4CE 133 1,089 0 21 Feb 2020
GraphLIME: Local Interpretable Model Explanations for Graph Neural Networks Q. Huang M. Yamada Yuan Tian Dinesh Singh Dawei Yin Yi-Ju Chang FAtt 75 354 0 17 Jan 2020
GNNExplainer: Generating Explanations for Graph Neural Networks Rex Ying Dylan Bourgeois Jiaxuan You Marinka Zitnik J. Leskovec LLMAG 140 1,319 0 10 Mar 2019
Fast Graph Representation Learning with PyTorch Geometric Matthias Fey J. E. Lenssen 3DH GNN 3DPC 220 4,336 0 06 Mar 2019
How Powerful are Graph Neural Networks? Keyulu Xu Weihua Hu J. Leskovec Stefanie Jegelka GNN 238 7,642 0 01 Oct 2018
Graph Convolutional Neural Networks for Web-Scale Recommender Systems Rex Ying Ruining He Kaifeng Chen Pong Eksombatchai William L. Hamilton J. Leskovec GNN BDL 257 3,537 0 06 Jun 2018
Neural Message Passing for Quantum Chemistry Justin Gilmer S. Schoenholz Patrick F. Riley Oriol Vinyals George E. Dahl 588 7,443 0 04 Apr 2017
"Why Should I Trust You?": Explaining the Predictions of Any Classifier Marco Tulio Ribeiro Sameer Singh Carlos Guestrin FAtt FaML 1.2K 16,954 0 16 Feb 2016