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INGREX: An Interactive Explanation Framework for Graph Neural Networks

INGREX: An Interactive Explanation Framework for Graph Neural Networks

3 November 2022
Tien-Cuong Bui
Van-Duc Le
Wen-Syan Li
S. Cha
ArXiv (abs)PDFHTML

Papers citing "INGREX: An Interactive Explanation Framework for Graph Neural Networks"

12 / 12 papers shown
Title
Toward Multiple Specialty Learners for Explaining GNNs via Online
  Knowledge Distillation
Toward Multiple Specialty Learners for Explaining GNNs via Online Knowledge Distillation
Tien-Cuong Bui
Van-Duc Le
Wen-Syan Li
S. Cha
63
3
0
20 Oct 2022
PGX: A Multi-level GNN Explanation Framework Based on Separate Knowledge
  Distillation Processes
PGX: A Multi-level GNN Explanation Framework Based on Separate Knowledge Distillation Processes
Tien-Cuong Bui
Wen-Syan Li
S. Cha
47
1
0
05 Aug 2022
Parameterized Explainer for Graph Neural Network
Parameterized Explainer for Graph Neural Network
Dongsheng Luo
Wei Cheng
Dongkuan Xu
Wenchao Yu
Bo Zong
Haifeng Chen
Xiang Zhang
149
563
0
09 Nov 2020
InterpretML: A Unified Framework for Machine Learning Interpretability
InterpretML: A Unified Framework for Machine Learning Interpretability
Harsha Nori
Samuel Jenkins
Paul Koch
R. Caruana
AI4CE
164
489
0
19 Sep 2019
Deep Graph Library: A Graph-Centric, Highly-Performant Package for Graph
  Neural Networks
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
AI4CEGNN
293
760
0
03 Sep 2019
GNNExplainer: Generating Explanations for Graph Neural Networks
GNNExplainer: Generating Explanations for Graph Neural Networks
Rex Ying
Dylan Bourgeois
Jiaxuan You
Marinka Zitnik
J. Leskovec
LLMAG
152
1,334
0
10 Mar 2019
Graph Neural Networks: A Review of Methods and Applications
Graph Neural Networks: A Review of Methods and Applications
Jie Zhou
Ganqu Cui
Shengding Hu
Zhengyan Zhang
Cheng Yang
Zhiyuan Liu
Lifeng Wang
Changcheng Li
Maosong Sun
AI4CEGNN
1.1K
5,551
0
20 Dec 2018
Graph Attention Networks
Graph Attention Networks
Petar Velickovic
Guillem Cucurull
Arantxa Casanova
Adriana Romero
Pietro Lio
Yoshua Bengio
GNN
484
20,265
0
30 Oct 2017
A Unified Approach to Interpreting Model Predictions
A Unified Approach to Interpreting Model Predictions
Scott M. Lundberg
Su-In Lee
FAtt
1.1K
22,090
0
22 May 2017
Billion-scale similarity search with GPUs
Billion-scale similarity search with GPUs
Jeff Johnson
Matthijs Douze
Hervé Jégou
259
3,741
0
28 Feb 2017
Semi-Supervised Classification with Graph Convolutional Networks
Semi-Supervised Classification with Graph Convolutional Networks
Thomas Kipf
Max Welling
GNNSSL
684
29,183
0
09 Sep 2016
"Why Should I Trust You?": Explaining the Predictions of Any Classifier
"Why Should I Trust You?": Explaining the Predictions of Any Classifier
Marco Tulio Ribeiro
Sameer Singh
Carlos Guestrin
FAttFaML
1.2K
17,071
0
16 Feb 2016
1