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Finding Diverse and Predictable Subgraphs for Graph Domain
  Generalization

Finding Diverse and Predictable Subgraphs for Graph Domain Generalization

19 June 2022
Junchi Yu
Jian Liang
Ran He
    OOD
ArXivPDFHTML

Papers citing "Finding Diverse and Predictable Subgraphs for Graph Domain Generalization"

50 / 56 papers shown
Title
Subgraph Aggregation for Out-of-Distribution Generalization on Graphs
Subgraph Aggregation for Out-of-Distribution Generalization on Graphs
Bowen Liu
Haoyang Li
Shuning Wang
Shuo Nie
Shanghang Zhang
OODD
CML
106
0
0
29 Oct 2024
A Survey of Deep Graph Learning under Distribution Shifts: from Graph Out-of-Distribution Generalization to Adaptation
A Survey of Deep Graph Learning under Distribution Shifts: from Graph Out-of-Distribution Generalization to Adaptation
Kexin Zhang
Shuhan Liu
Song Wang
Weili Shi
Chen Chen
Pan Li
Sheng Li
Jundong Li
Kaize Ding
OOD
91
3
0
25 Oct 2024
How to Find Your Friendly Neighborhood: Graph Attention Design with
  Self-Supervision
How to Find Your Friendly Neighborhood: Graph Attention Design with Self-Supervision
Dongkwan Kim
Alice Oh
SSL
GNN
75
258
0
11 Apr 2022
Equivariant Graph Mechanics Networks with Constraints
Equivariant Graph Mechanics Networks with Constraints
Wen-bing Huang
J. Han
Yu Rong
Tingyang Xu
Gang Hua
Junzhou Huang
AI4CE
49
79
0
12 Mar 2022
Out-Of-Distribution Generalization on Graphs: A Survey
Out-Of-Distribution Generalization on Graphs: A Survey
Haoyang Li
Xin Eric Wang
Ziwei Zhang
Wenwu Zhu
OOD
CML
68
99
0
16 Feb 2022
Discovering Invariant Rationales for Graph Neural Networks
Discovering Invariant Rationales for Graph Neural Networks
Yingmin Wu
Xiang Wang
An Zhang
Xiangnan He
Tat-Seng Chua
OOD
AI4CE
132
226
0
30 Jan 2022
Improving Subgraph Recognition with Variational Graph Information
  Bottleneck
Improving Subgraph Recognition with Variational Graph Information Bottleneck
Junchi Yu
Jie Cao
Ran He
33
54
0
18 Dec 2021
Graph Structure Learning with Variational Information Bottleneck
Graph Structure Learning with Variational Information Bottleneck
Qingyun Sun
Jianxin Li
Hao Peng
Hongzhi Zhang
Xingcheng Fu
Cheng Ji
Philip S. Yu
57
160
0
16 Dec 2021
Shift-Robust GNNs: Overcoming the Limitations of Localized Graph
  Training Data
Shift-Robust GNNs: Overcoming the Limitations of Localized Graph Training Data
Qi Zhu
Natalia Ponomareva
Jiawei Han
Bryan Perozzi
OOD
46
110
0
02 Aug 2021
An Information-theoretic Approach to Distribution Shifts
An Information-theoretic Approach to Distribution Shifts
Marco Federici
Ryota Tomioka
Patrick Forré
OOD
53
20
0
07 Jun 2021
Recognizing Predictive Substructures with Subgraph Information
  Bottleneck
Recognizing Predictive Substructures with Subgraph Information Bottleneck
Junchi Yu
Tingyang Xu
Yu Rong
Yatao Bian
Junzhou Huang
Ran He
33
44
0
20 Mar 2021
Size-Invariant Graph Representations for Graph Classification
  Extrapolations
Size-Invariant Graph Representations for Graph Classification Extrapolations
Beatrice Bevilacqua
Yangze Zhou
Bruno Ribeiro
OOD
72
110
0
08 Mar 2021
Generalizing to Unseen Domains: A Survey on Domain Generalization
Generalizing to Unseen Domains: A Survey on Domain Generalization
Jindong Wang
Cuiling Lan
Chang-Shu Liu
Yidong Ouyang
Tao Qin
Wang Lu
Yiqiang Chen
Wenjun Zeng
Philip S. Yu
OOD
146
1,198
0
02 Mar 2021
Graph Convolution for Semi-Supervised Classification: Improved Linear
  Separability and Out-of-Distribution Generalization
Graph Convolution for Semi-Supervised Classification: Improved Linear Separability and Out-of-Distribution Generalization
Aseem Baranwal
Kimon Fountoulakis
Aukosh Jagannath
OODD
81
75
0
13 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
110
1,202
0
04 Nov 2020
Graph Information Bottleneck
Graph Information Bottleneck
Tailin Wu
Hongyu Ren
Pan Li
J. Leskovec
AAML
123
231
0
24 Oct 2020
Graph Information Bottleneck for Subgraph Recognition
Graph Information Bottleneck for Subgraph Recognition
Junchi Yu
Tingyang Xu
Yu Rong
Yatao Bian
Junzhou Huang
Ran He
34
154
0
12 Oct 2020
Energy-based Out-of-distribution Detection
Energy-based Out-of-distribution Detection
Weitang Liu
Xiaoyun Wang
John Douglas Owens
Yixuan Li
OODD
177
1,332
0
08 Oct 2020
Transfer Learning of Graph Neural Networks with Ego-graph Information
  Maximization
Transfer Learning of Graph Neural Networks with Ego-graph Information Maximization
Qi Zhu
Carl Yang
Yidan Xu
Haonan Wang
Chao Zhang
Jiawei Han
60
118
0
11 Sep 2020
Learning to Learn with Variational Information Bottleneck for Domain
  Generalization
Learning to Learn with Variational Information Bottleneck for Domain Generalization
Yingjun Du
Jun Xu
Huan Xiong
Qiang Qiu
Xiantong Zhen
Cees G. M. Snoek
Ling Shao
BDL
OOD
50
165
0
15 Jul 2020
Simple and Deep Graph Convolutional Networks
Simple and Deep Graph Convolutional Networks
Ming Chen
Zhewei Wei
Zengfeng Huang
Bolin Ding
Yaliang Li
GNN
72
1,466
0
04 Jul 2020
Iterative Deep Graph Learning for Graph Neural Networks: Better and
  Robust Node Embeddings
Iterative Deep Graph Learning for Graph Neural Networks: Better and Robust Node Embeddings
Yu Chen
Lingfei Wu
Mohammed J Zaki
59
415
0
21 Jun 2020
Graph Structure Learning for Robust Graph Neural Networks
Graph Structure Learning for Robust Graph Neural Networks
Wei Jin
Yao Ma
Xiaorui Liu
Xianfeng Tang
Suhang Wang
Jiliang Tang
OOD
AAML
44
698
0
20 May 2020
Open Graph Benchmark: Datasets for Machine Learning on Graphs
Open Graph Benchmark: Datasets for Machine Learning on Graphs
Weihua Hu
Matthias Fey
Marinka Zitnik
Yuxiao Dong
Hongyu Ren
Bowen Liu
Michele Catasta
J. Leskovec
155
2,687
0
02 May 2020
Learning to Learn Single Domain Generalization
Learning to Learn Single Domain Generalization
Fengchun Qiao
Long Zhao
Xi Peng
OOD
102
438
0
30 Mar 2020
Out-of-Distribution Generalization via Risk Extrapolation (REx)
Out-of-Distribution Generalization via Risk Extrapolation (REx)
David M. Krueger
Ethan Caballero
J. Jacobsen
Amy Zhang
Jonathan Binas
Dinghuai Zhang
Rémi Le Priol
Aaron Courville
OOD
277
921
0
02 Mar 2020
Rumor Detection on Social Media with Bi-Directional Graph Convolutional
  Networks
Rumor Detection on Social Media with Bi-Directional Graph Convolutional Networks
Tian Bian
Xi Xiao
Tingyang Xu
P. Zhao
Wenbing Huang
Yu Rong
Junzhou Huang
GNN
29
593
0
17 Jan 2020
Your Classifier is Secretly an Energy Based Model and You Should Treat
  it Like One
Your Classifier is Secretly an Energy Based Model and You Should Treat it Like One
Will Grathwohl
Kuan-Chieh Wang
J. Jacobsen
David Duvenaud
Mohammad Norouzi
Kevin Swersky
VLM
58
536
0
06 Dec 2019
Distributionally Robust Neural Networks for Group Shifts: On the
  Importance of Regularization for Worst-Case Generalization
Distributionally Robust Neural Networks for Group Shifts: On the Importance of Regularization for Worst-Case Generalization
Shiori Sagawa
Pang Wei Koh
Tatsunori B. Hashimoto
Percy Liang
OOD
36
1,217
0
20 Nov 2019
Domain Generalization Using a Mixture of Multiple Latent Domains
Domain Generalization Using a Mixture of Multiple Latent Domains
Toshihiko Matsuura
Tatsuya Harada
OOD
48
324
0
18 Nov 2019
Graph-Revised Convolutional Network
Graph-Revised Convolutional Network
Donghan Yu
Ruohong Zhang
Zhengbao Jiang
Yuexin Wu
Yiming Yang
GNN
31
98
0
17 Nov 2019
Multi-scale Attributed Node Embedding
Multi-scale Attributed Node Embedding
Benedek Rozemberczki
Carl Allen
Rik Sarkar
GNN
222
849
0
28 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
62
1,323
0
25 Jul 2019
Invariant Risk Minimization
Invariant Risk Minimization
Martín Arjovsky
Léon Bottou
Ishaan Gulrajani
David Lopez-Paz
OOD
135
2,190
0
05 Jul 2019
Graph U-Nets
Graph U-Nets
Hongyang Gao
Shuiwang Ji
AI4CE
SSL
SSeg
GNN
56
1,073
0
11 May 2019
Understanding Attention and Generalization in Graph Neural Networks
Understanding Attention and Generalization in Graph Neural Networks
Boris Knyazev
Graham W. Taylor
Mohamed R. Amer
GNN
59
338
0
08 May 2019
Semi-Supervised Graph Classification: A Hierarchical Graph Perspective
Semi-Supervised Graph Classification: A Hierarchical Graph Perspective
Jia Li
Yu Rong
Hong Cheng
Helen Meng
Wen-bing Huang
Junzhou Huang
26
149
0
10 Apr 2019
Learning Discrete Structures for Graph Neural Networks
Learning Discrete Structures for Graph Neural Networks
Luca Franceschi
Mathias Niepert
Massimiliano Pontil
X. He
GNN
43
411
0
28 Mar 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
104
1,300
0
10 Mar 2019
Learning Robust Representations by Projecting Superficial Statistics Out
Learning Robust Representations by Projecting Superficial Statistics Out
Haohan Wang
Zexue He
Zachary Chase Lipton
Eric Xing
OOD
50
234
0
02 Mar 2019
EvolveGCN: Evolving Graph Convolutional Networks for Dynamic Graphs
EvolveGCN: Evolving Graph Convolutional Networks for Dynamic Graphs
A. Pareja
Giacomo Domeniconi
Jie Chen
Tengfei Ma
Toyotaro Suzumura
H. Kanezashi
Tim Kaler
Tao B. Schardl
Charles E. Leisersen
GNN
80
1,051
0
26 Feb 2019
Graph Neural Networks for Social Recommendation
Graph Neural Networks for Social Recommendation
Wenqi Fan
Yao Ma
Qing Li
Yuan He
Yue Zhao
Jiliang Tang
Dawei Yin
145
1,873
0
19 Feb 2019
Simplifying Graph Convolutional Networks
Simplifying Graph Convolutional Networks
Felix Wu
Tianyi Zhang
Amauri Souza
Christopher Fifty
Tao Yu
Kilian Q. Weinberger
GNN
138
3,149
0
19 Feb 2019
Predict then Propagate: Graph Neural Networks meet Personalized PageRank
Predict then Propagate: Graph Neural Networks meet Personalized PageRank
Johannes Klicpera
Aleksandar Bojchevski
Stephan Günnemann
GNN
168
1,674
0
14 Oct 2018
Robust Optimization over Multiple Domains
Robust Optimization over Multiple Domains
Qi Qian
Shenghuo Zhu
Jiasheng Tang
Rong Jin
Baigui Sun
Hao Li
OOD
38
71
0
19 May 2018
A comparative study of fairness-enhancing interventions in machine
  learning
A comparative study of fairness-enhancing interventions in machine learning
Sorelle A. Friedler
C. Scheidegger
Suresh Venkatasubramanian
Sonam Choudhary
Evan P. Hamilton
Derek Roth
FaML
83
639
0
13 Feb 2018
Junction Tree Variational Autoencoder for Molecular Graph Generation
Junction Tree Variational Autoencoder for Molecular Graph Generation
Wengong Jin
Regina Barzilay
Tommi Jaakkola
284
1,358
0
12 Feb 2018
MINE: Mutual Information Neural Estimation
MINE: Mutual Information Neural Estimation
Mohamed Ishmael Belghazi
A. Baratin
Sai Rajeswar
Sherjil Ozair
Yoshua Bengio
Aaron Courville
R. Devon Hjelm
DRL
118
1,264
0
12 Jan 2018
Graph Attention Networks
Graph Attention Networks
Petar Velickovic
Guillem Cucurull
Arantxa Casanova
Adriana Romero
Pietro Lio
Yoshua Bengio
GNN
278
19,902
0
30 Oct 2017
Inductive Representation Learning on Large Graphs
Inductive Representation Learning on Large Graphs
William L. Hamilton
Z. Ying
J. Leskovec
332
15,066
0
07 Jun 2017
12
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