Deconfounding to Explanation Evaluation in Graph Neural Networks

21 January 2022

Xiang Wang

Papers citing "Deconfounding to Explanation Evaluation in Graph Neural Networks"

34 / 34 papers shown

Title
Generative Adversarial Networks Gilad Cohen Raja Giryes GAN 177 30,069 0 01 Mar 2022
Counterfactual Zero-Shot and Open-Set Visual Recognition Zhongqi Yue Tan Wang Hanwang Zhang Qianru Sun Xiansheng Hua BDL 200 193 0 01 Mar 2021
On Explainability of Graph Neural Networks via Subgraph Explorations Hao Yuan Haiyang Yu Jie Wang Kang Li Shuiwang Ji FAtt 62 383 0 09 Feb 2021
Parameterized Explainer for Graph Neural Network Dongsheng Luo Wei Cheng Dongkuan Xu Wenchao Yu Bo Zong Haifeng Chen Xiang Zhang 123 546 0 09 Nov 2020
Feature Removal Is a Unifying Principle for Model Explanation Methods Ian Covert Scott M. Lundberg Su-In Lee FAtt 92 33 0 06 Nov 2020
Interpretation of NLP models through input marginalization Siwon Kim Jihun Yi Eunji Kim Sungroh Yoon MILM FAtt 50 58 0 27 Oct 2020
Contrastive Graph Neural Network Explanation Lukas Faber A. K. Moghaddam Roger Wattenhofer 62 36 0 26 Oct 2020
PGM-Explainer: Probabilistic Graphical Model Explanations for Graph Neural Networks Minh Nhat Vu My T. Thai BDL 50 330 0 12 Oct 2020
Interpreting Graph Neural Networks for NLP With Differentiable Edge Masking Michael Schlichtkrull Nicola De Cao Ivan Titov AI4CE 55 217 0 01 Oct 2020
Higher-Order Explanations of Graph Neural Networks via Relevant Walks Thomas Schnake Oliver Eberle Jonas Lederer Shinichi Nakajima Kristof T. Schütt Klaus-Robert Muller G. Montavon 90 218 0 05 Jun 2020
XGNN: Towards Model-Level Explanations of Graph Neural Networks Haonan Yuan Jiliang Tang Xia Hu Shuiwang Ji 61 393 0 03 Jun 2020
RelEx: A Model-Agnostic Relational Model Explainer Yue Zhang David DeFazio Arti Ramesh 29 106 0 30 May 2020
Benchmarking Graph Neural Networks Vijay Prakash Dwivedi Chaitanya K. Joshi Anh Tuan Luu T. Laurent Yoshua Bengio Xavier Bresson 299 931 0 02 Mar 2020
ASAP: Adaptive Structure Aware Pooling for Learning Hierarchical Graph Representations Ekagra Ranjan Soumya Sanyal Partha P. Talukdar GNN 111 330 0 18 Nov 2019
CXPlain: Causal Explanations for Model Interpretation under Uncertainty Patrick Schwab W. Karlen FAtt CML 104 208 0 27 Oct 2019
Explaining image classifiers by removing input features using generative models Chirag Agarwal Anh Totti Nguyen FAtt 35 15 0 09 Oct 2019
Explainability Techniques for Graph Convolutional Networks Federico Baldassarre Hossein Azizpour GNN FAtt 148 264 0 31 May 2019
GNNExplainer: Generating Explanations for Graph Neural Networks Rex Ying Dylan Bourgeois Jiaxuan You Marinka Zitnik J. Leskovec LLMAG 111 1,300 0 10 Mar 2019
Fast Graph Representation Learning with PyTorch Geometric Matthias Fey J. E. Lenssen 3DH GNN 3DPC 169 4,303 0 06 Mar 2019
Robustly Disentangled Causal Mechanisms: Validating Deep Representations for Interventional Robustness Raphael Suter Ðorðe Miladinovic Bernhard Schölkopf Stefan Bauer CML OOD DRL 103 160 0 31 Oct 2018
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding Jacob Devlin Ming-Wei Chang Kenton Lee Kristina Toutanova VLM SSL SSeg 1.0K 93,936 0 11 Oct 2018
Explaining Image Classifiers by Counterfactual Generation C. Chang Elliot Creager Anna Goldenberg David Duvenaud VLM 48 265 0 20 Jul 2018
Adversarial Attack on Graph Structured Data H. Dai Hui Li Tian Tian Xin Huang L. Wang Jun Zhu Le Song GNN AAML OOD 75 767 0 06 Jun 2018
Constrained Graph Variational Autoencoders for Molecule Design Qi Liu Miltiadis Allamanis Marc Brockschmidt Alexander L. Gaunt BDL 53 453 0 23 May 2018
Adversarial Attacks on Neural Networks for Graph Data Daniel Zügner Amir Akbarnejad Stephan Günnemann GNN AAML OOD 113 1,060 0 21 May 2018
SplineCNN: Fast Geometric Deep Learning with Continuous B-Spline Kernels Matthias Fey J. E. Lenssen F. Weichert H. Müller 3DPC 113 440 0 24 Nov 2017
Graph Attention Networks Petar Velickovic Guillem Cucurull Arantxa Casanova Adriana Romero Pietro Lio Yoshua Bengio GNN 348 19,991 0 30 Oct 2017
Inductive Representation Learning on Large Graphs William L. Hamilton Z. Ying J. Leskovec 403 15,066 0 07 Jun 2017
Real Time Image Saliency for Black Box Classifiers P. Dabkowski Y. Gal 55 586 0 22 May 2017
Interpretable Explanations of Black Boxes by Meaningful Perturbation Ruth C. Fong Andrea Vedaldi FAtt AAML 55 1,514 0 11 Apr 2017
Geometric deep learning on graphs and manifolds using mixture model CNNs Federico Monti Davide Boscaini Jonathan Masci Emanuele Rodolà Jan Svoboda M. Bronstein GNN 364 1,817 0 25 Nov 2016
Variational Graph Auto-Encoders Thomas Kipf Max Welling GNN BDL SSL CML 107 3,559 0 21 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 221 19,796 0 07 Oct 2016
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 896 149,474 0 22 Dec 2014