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Improving the interpretability of GNN predictions through
  conformal-based graph sparsification

Improving the interpretability of GNN predictions through conformal-based graph sparsification

18 April 2024
Pablo Sánchez-Martín
Kinaan Aamir Khan
Isabel Valera
ArXivPDFHTML

Papers citing "Improving the interpretability of GNN predictions through conformal-based graph sparsification"

28 / 28 papers shown
Title
Stackelberg Actor-Critic: Game-Theoretic Reinforcement Learning
  Algorithms
Stackelberg Actor-Critic: Game-Theoretic Reinforcement Learning Algorithms
Liyuan Zheng
Tanner Fiez
Zane Alumbaugh
Benjamin J. Chasnov
Lillian J. Ratliff
OffRL
80
40
0
25 Sep 2021
A Gentle Introduction to Conformal Prediction and Distribution-Free
  Uncertainty Quantification
A Gentle Introduction to Conformal Prediction and Distribution-Free Uncertainty Quantification
Anastasios Nikolas Angelopoulos
Stephen Bates
OOD
201
617
0
15 Jul 2021
A Bi-Level Framework for Learning to Solve Combinatorial Optimization on
  Graphs
A Bi-Level Framework for Learning to Solve Combinatorial Optimization on Graphs
Runzhong Wang
Zhigang Hua
Gan Liu
Jiayi Zhang
Junchi Yan
Feng Qi
Shuang Yang
Jun Zhou
Xiaokang Yang
60
42
0
09 Jun 2021
Few-Shot Graph Learning for Molecular Property Prediction
Few-Shot Graph Learning for Molecular Property Prediction
Zhichun Guo
Chuxu Zhang
Wenhao Yu
John E. Herr
Olaf Wiest
Meng Jiang
Nitesh Chawla
AI4CE
153
175
0
16 Feb 2021
On Explainability of Graph Neural Networks via Subgraph Explorations
On Explainability of Graph Neural Networks via Subgraph Explorations
Hao Yuan
Haiyang Yu
Jie Wang
Kang Li
Shuiwang Ji
FAtt
83
390
0
09 Feb 2021
Graph Neural Networks in Recommender Systems: A Survey
Graph Neural Networks in Recommender Systems: A Survey
Shiwen Wu
Fei Sun
Wentao Zhang
Xu Xie
Tengjiao Wang
GNN
135
1,228
0
04 Nov 2020
Uncertainty Sets for Image Classifiers using Conformal Prediction
Uncertainty Sets for Image Classifiers using Conformal Prediction
Anastasios Nikolas Angelopoulos
Stephen Bates
Jitendra Malik
Michael I. Jordan
UQCV
203
334
0
29 Sep 2020
Simple and Deep Graph Convolutional Networks
Simple and Deep Graph Convolutional Networks
Ming Chen
Zhewei Wei
Zengfeng Huang
Bolin Ding
Yaliang Li
GNN
119
1,485
0
04 Jul 2020
Bayesian Graph Neural Networks with Adaptive Connection Sampling
Bayesian Graph Neural Networks with Adaptive Connection Sampling
Arman Hasanzadeh
Ehsan Hajiramezanali
Shahin Boluki
Mingyuan Zhou
N. Duffield
Krishna R. Narayanan
Xiaoning Qian
BDL
46
118
0
07 Jun 2020
XGNN: Towards Model-Level Explanations of Graph Neural Networks
XGNN: Towards Model-Level Explanations of Graph Neural Networks
Haonan Yuan
Jiliang Tang
Xia Hu
Shuiwang Ji
78
399
0
03 Jun 2020
Classification with Valid and Adaptive Coverage
Classification with Valid and Adaptive Coverage
Yaniv Romano
Matteo Sesia
Emmanuel J. Candès
387
324
0
03 Jun 2020
Principal Neighbourhood Aggregation for Graph Nets
Principal Neighbourhood Aggregation for Graph Nets
Gabriele Corso
Luca Cavalleri
Dominique Beaini
Pietro Lio
Petar Velickovic
GNN
109
667
0
12 Apr 2020
Reinforcement Learning for Combinatorial Optimization: A Survey
Reinforcement Learning for Combinatorial Optimization: A Survey
Nina Mazyavkina
S. Sviridov
Sergei Ivanov
Evgeny Burnaev
92
623
0
07 Mar 2020
Overlapping Community Detection with Graph Neural Networks
Overlapping Community Detection with Graph Neural Networks
Oleksandr Shchur
Stephan Günnemann
GNN
63
131
0
26 Sep 2019
DropEdge: Towards Deep Graph Convolutional Networks on Node
  Classification
DropEdge: Towards Deep Graph Convolutional Networks on Node Classification
Yu Rong
Wenbing Huang
Tingyang Xu
Junzhou Huang
107
1,339
0
25 Jul 2019
What graph neural networks cannot learn: depth vs width
What graph neural networks cannot learn: depth vs width
Andreas Loukas
GNN
84
299
0
06 Jul 2019
Graph U-Nets
Graph U-Nets
Hongyang Gao
Shuiwang Ji
AI4CE
SSL
SSeg
GNN
129
1,090
0
11 May 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
142
1,323
0
10 Mar 2019
Fast Graph Representation Learning with PyTorch Geometric
Fast Graph Representation Learning with PyTorch Geometric
Matthias Fey
J. E. Lenssen
3DH
GNN
3DPC
226
4,339
0
06 Mar 2019
A Comprehensive Survey on Graph Neural Networks
A Comprehensive Survey on Graph Neural Networks
Zonghan Wu
Shirui Pan
Fengwen Chen
Guodong Long
Chengqi Zhang
Philip S. Yu
FaML
GNN
AI4TS
AI4CE
773
8,533
0
03 Jan 2019
Towards Sparse Hierarchical Graph Classifiers
Towards Sparse Hierarchical Graph Classifiers
Cătălina Cangea
Petar Velickovic
Nikola Jovanović
Thomas Kipf
Pietro Lio
GNN
184
259
0
03 Nov 2018
How Powerful are Graph Neural Networks?
How Powerful are Graph Neural Networks?
Keyulu Xu
Weihua Hu
J. Leskovec
Stefanie Jegelka
GNN
240
7,653
0
01 Oct 2018
Graph Attention Networks
Graph Attention Networks
Petar Velickovic
Guillem Cucurull
Arantxa Casanova
Adriana Romero
Pietro Lio
Yoshua Bengio
GNN
479
20,138
0
30 Oct 2017
Proximal Policy Optimization Algorithms
Proximal Policy Optimization Algorithms
John Schulman
Filip Wolski
Prafulla Dhariwal
Alec Radford
Oleg Klimov
OffRL
499
19,065
0
20 Jul 2017
Neural Message Passing for Quantum Chemistry
Neural Message Passing for Quantum Chemistry
Justin Gilmer
S. Schoenholz
Patrick F. Riley
Oriol Vinyals
George E. Dahl
593
7,455
0
04 Apr 2017
Geometric deep learning: going beyond Euclidean data
Geometric deep learning: going beyond Euclidean data
M. Bronstein
Joan Bruna
Yann LeCun
Arthur Szlam
P. Vandergheynst
GNN
808
3,287
0
24 Nov 2016
Semi-Supervised Classification with Graph Convolutional Networks
Semi-Supervised Classification with Graph Convolutional Networks
Thomas Kipf
Max Welling
GNN
SSL
626
29,051
0
09 Sep 2016
Algorithms for multi-armed bandit problems
Algorithms for multi-armed bandit problems
Volodymyr Kuleshov
Doina Precup
134
350
0
25 Feb 2014
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