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Shift-Robust GNNs: Overcoming the Limitations of Localized Graph
  Training Data

Shift-Robust GNNs: Overcoming the Limitations of Localized Graph Training Data

2 August 2021
Qi Zhu
Natalia Ponomareva
Jiawei Han
Bryan Perozzi
    OOD
ArXivPDFHTML

Papers citing "Shift-Robust GNNs: Overcoming the Limitations of Localized Graph Training Data"

13 / 13 papers shown
Title
Efficient Data Selection for Training Genomic Perturbation Models
Efficient Data Selection for Training Genomic Perturbation Models
G. Panagopoulos
J. Lutzeyer
Sofiane Ennadir
Michalis Vazirgiannis
Jun Pang
89
0
0
18 Mar 2025
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 R. Li
Jundong Li
Kaize Ding
OOD
45
2
0
25 Oct 2024
Control the GNN: Utilizing Neural Controller with Lyapunov Stability for Test-Time Feature Reconstruction
Control the GNN: Utilizing Neural Controller with Lyapunov Stability for Test-Time Feature Reconstruction
Jielong Yang
Rui Ding
Feng Ji
Hongbin Wang
Linbo Xie
30
0
0
13 Oct 2024
Leveraging Invariant Principle for Heterophilic Graph Structure Distribution Shifts
Leveraging Invariant Principle for Heterophilic Graph Structure Distribution Shifts
Jinluan Yang
Zhengyu Chen
Teng Xiao
Wenqiao Zhang
Yong Lin
Kun Kuang
51
1
0
18 Aug 2024
Conditional Shift-Robust Conformal Prediction for Graph Neural Network
Conditional Shift-Robust Conformal Prediction for Graph Neural Network
Akansha Agrawal
UQCV
45
1
0
20 May 2024
Everything Perturbed All at Once: Enabling Differentiable Graph Attacks
Everything Perturbed All at Once: Enabling Differentiable Graph Attacks
Haoran Liu
Bokun Wang
Jianling Wang
Xiangjue Dong
Tianbao Yang
James Caverlee
AAML
26
3
0
29 Aug 2023
Individual and Structural Graph Information Bottlenecks for
  Out-of-Distribution Generalization
Individual and Structural Graph Information Bottlenecks for Out-of-Distribution Generalization
Ling Yang
Jiayi Zheng
Heyuan Wang
Zhongyi Liu
Zhilin Huang
Shenda Hong
Wentao Zhang
Bin Cui
14
13
0
28 Jun 2023
GraphGLOW: Universal and Generalizable Structure Learning for Graph
  Neural Networks
GraphGLOW: Universal and Generalizable Structure Learning for Graph Neural Networks
Wentao Zhao
Qitian Wu
Chenxiao Yang
Junchi Yan
17
12
0
20 Jun 2023
Curriculum Graph Machine Learning: A Survey
Curriculum Graph Machine Learning: A Survey
Haoyang Li
Xin Eric Wang
Wenwu Zhu
15
16
0
06 Feb 2023
Beyond Ensemble Averages: Leveraging Climate Model Ensembles for
  Subseasonal Forecasting
Beyond Ensemble Averages: Leveraging Climate Model Ensembles for Subseasonal Forecasting
Elena Orlova
Haokun Liu
Raphael Rossellini
B. Cash
Rebecca Willett
19
3
0
29 Nov 2022
GOOD: A Graph Out-of-Distribution Benchmark
GOOD: A Graph Out-of-Distribution Benchmark
Shurui Gui
Xiner Li
Limei Wang
Shuiwang Ji
OOD
22
115
0
16 Jun 2022
Grale: Designing Networks for Graph Learning
Grale: Designing Networks for Graph Learning
Jonathan J. Halcrow
A. Mosoi
Sam Ruth
Bryan Perozzi
GNN
63
46
0
23 Jul 2020
Domain Adaptation: Learning Bounds and Algorithms
Domain Adaptation: Learning Bounds and Algorithms
Yishay Mansour
M. Mohri
Afshin Rostamizadeh
179
786
0
19 Feb 2009
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