Saved in:
| Main Authors: | Zhang, Simon, DeMilt, Ryan P., Jin, Kun, Xia, Cathy H. |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2604.08404 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Invariant Graph Transformer for Out-of-Distribution Generalization
by: Liao, Tianyin, et al.
Published: (2025)
by: Liao, Tianyin, et al.
Published: (2025)
Enhancing Distribution and Label Consistency for Graph Out-of-Distribution Generalization
by: Wang, Song, et al.
Published: (2025)
by: Wang, Song, et al.
Published: (2025)
Invariant Graph Learning Meets Information Bottleneck for Out-of-Distribution Generalization
by: Mao, Wenyu, et al.
Published: (2024)
by: Mao, Wenyu, et al.
Published: (2024)
GOLD: Graph Out-of-Distribution Detection via Implicit Adversarial Latent Generation
by: Wang, Danny, et al.
Published: (2025)
by: Wang, Danny, et al.
Published: (2025)
Unlocking Out-of-Distribution Generalization in Dynamics through Physics-Guided Augmentation
by: Xu, Fan, et al.
Published: (2025)
by: Xu, Fan, et al.
Published: (2025)
Score-based Conditional Out-of-Distribution Augmentation for Graph Covariate Shift
by: Wang, Bohan, et al.
Published: (2024)
by: Wang, Bohan, et al.
Published: (2024)
Subgraph Aggregation for Out-of-Distribution Generalization on Graphs
by: Liu, Bowen, et al.
Published: (2024)
by: Liu, Bowen, et al.
Published: (2024)
Out-of-Distribution Optimality of Invariant Risk Minimization
by: Toyota, Shoji, et al.
Published: (2023)
by: Toyota, Shoji, et al.
Published: (2023)
Out-of-Distribution Data: An Acquaintance of Adversarial Examples -- A Survey
by: Karunanayake, Naveen, et al.
Published: (2024)
by: Karunanayake, Naveen, et al.
Published: (2024)
Generative Risk Minimization for Out-of-Distribution Generalization on Graphs
by: Wang, Song, et al.
Published: (2025)
by: Wang, Song, et al.
Published: (2025)
Leveraging Invariant Principle for Heterophilic Graph Structure Distribution Shifts
by: Yang, Jinluan, et al.
Published: (2024)
by: Yang, Jinluan, et al.
Published: (2024)
Time-Series Forecasting for Out-of-Distribution Generalization Using Invariant Learning
by: Liu, Haoxin, et al.
Published: (2024)
by: Liu, Haoxin, et al.
Published: (2024)
Out-of-Distribution Generalization in Graph Foundation Models
by: Li, Haoyang, et al.
Published: (2026)
by: Li, Haoyang, et al.
Published: (2026)
When Noisy Labels Meet Class Imbalance on Graphs: A Graph Augmentation Method with LLM and Pseudo Label
by: Xia, Riting, et al.
Published: (2025)
by: Xia, Riting, et al.
Published: (2025)
Unifying Invariant and Variant Features for Graph Out-of-Distribution via Probability of Necessity and Sufficiency
by: Chen, Xuexin, et al.
Published: (2024)
by: Chen, Xuexin, et al.
Published: (2024)
Generalizing Graph Neural Networks on Out-Of-Distribution Graphs
by: Fan, Shaohua, et al.
Published: (2021)
by: Fan, Shaohua, et al.
Published: (2021)
Invariant Correlation of Representation with Label: Enhancing Domain Generalization in Noisy Environments
by: Jin, Gaojie, et al.
Published: (2024)
by: Jin, Gaojie, et al.
Published: (2024)
Optimal Ridge Regularization for Out-of-Distribution Prediction
by: Patil, Pratik, et al.
Published: (2024)
by: Patil, Pratik, et al.
Published: (2024)
Out-of-Distribution Generalization on Graphs via Progressive Inference
by: Xu, Yiming, et al.
Published: (2025)
by: Xu, Yiming, et al.
Published: (2025)
Exploring Graph-Transformer Out-of-Distribution Generalization Abilities
by: Niv, Itay, et al.
Published: (2025)
by: Niv, Itay, et al.
Published: (2025)
Graph Structure and Feature Extrapolation for Out-of-Distribution Generalization
by: Li, Xiner, et al.
Published: (2023)
by: Li, Xiner, et al.
Published: (2023)
Structural Entropy Guided Unsupervised Graph Out-Of-Distribution Detection
by: Hou, Yue, et al.
Published: (2025)
by: Hou, Yue, et al.
Published: (2025)
On the Escaping Efficiency of Distributed Adversarial Training Algorithms
by: Cao, Ying, et al.
Published: (2025)
by: Cao, Ying, et al.
Published: (2025)
Few-Shot Graph Out-of-Distribution Detection with LLMs
by: Xu, Haoyan, et al.
Published: (2025)
by: Xu, Haoyan, et al.
Published: (2025)
When and How Does In-Distribution Label Help Out-of-Distribution Detection?
by: Du, Xuefeng, et al.
Published: (2024)
by: Du, Xuefeng, et al.
Published: (2024)
IDEA: Invariant Defense for Graph Adversarial Robustness
by: Tao, Shuchang, et al.
Published: (2023)
by: Tao, Shuchang, et al.
Published: (2023)
Generative Adversarial Evasion and Out-of-Distribution Detection for UAV Cyber-Attacks
by: Panda, Deepak Kumar, et al.
Published: (2025)
by: Panda, Deepak Kumar, et al.
Published: (2025)
Quantifying Explanation Quality in Graph Neural Networks using Out-of-Distribution Generalization
by: Zhang, Ding, et al.
Published: (2026)
by: Zhang, Ding, et al.
Published: (2026)
Disentangled Graph Prompting for Out-Of-Distribution Detection
by: Yang, Cheng, et al.
Published: (2026)
by: Yang, Cheng, et al.
Published: (2026)
A Survey of Deep Graph Learning under Distribution Shifts: from Graph Out-of-Distribution Generalization to Adaptation
by: Zhang, Kexin, et al.
Published: (2024)
by: Zhang, Kexin, et al.
Published: (2024)
Beyond Generalization: A Survey of Out-Of-Distribution Adaptation on Graphs
by: Liu, Shuhan, et al.
Published: (2024)
by: Liu, Shuhan, et al.
Published: (2024)
Invariant Link Selector for Spatial-Temporal Out-of-Distribution Problem
by: Tieu, Katherine, et al.
Published: (2025)
by: Tieu, Katherine, et al.
Published: (2025)
Out-of-Distribution Generalized Dynamic Graph Neural Network with Disentangled Intervention and Invariance Promotion
by: Zhang, Zeyang, et al.
Published: (2023)
by: Zhang, Zeyang, et al.
Published: (2023)
DIVE: Subgraph Disagreement for Graph Out-of-Distribution Generalization
by: Sun, Xin, et al.
Published: (2024)
by: Sun, Xin, et al.
Published: (2024)
Benign Overfitting in Out-of-Distribution Generalization of Linear Models
by: Tang, Shange, et al.
Published: (2024)
by: Tang, Shange, et al.
Published: (2024)
Learning Invariant Representations of Graph Neural Networks via Cluster Generalization
by: Xia, Donglin, et al.
Published: (2024)
by: Xia, Donglin, et al.
Published: (2024)
Out-of-Distribution Graph Models Merging
by: Wang, Yidi, et al.
Published: (2025)
by: Wang, Yidi, et al.
Published: (2025)
GOODAT: Towards Test-time Graph Out-of-Distribution Detection
by: Wang, Luzhi, et al.
Published: (2024)
by: Wang, Luzhi, et al.
Published: (2024)
Principled Out-of-Distribution Generalization via Simplicity
by: Ge, Jiawei, et al.
Published: (2025)
by: Ge, Jiawei, et al.
Published: (2025)
Pruning Spurious Subgraphs for Graph Out-of-Distribution Generalization
by: Yao, Tianjun, et al.
Published: (2025)
by: Yao, Tianjun, et al.
Published: (2025)
Similar Items
-
Invariant Graph Transformer for Out-of-Distribution Generalization
by: Liao, Tianyin, et al.
Published: (2025) -
Enhancing Distribution and Label Consistency for Graph Out-of-Distribution Generalization
by: Wang, Song, et al.
Published: (2025) -
Invariant Graph Learning Meets Information Bottleneck for Out-of-Distribution Generalization
by: Mao, Wenyu, et al.
Published: (2024) -
GOLD: Graph Out-of-Distribution Detection via Implicit Adversarial Latent Generation
by: Wang, Danny, et al.
Published: (2025) -
Unlocking Out-of-Distribution Generalization in Dynamics through Physics-Guided Augmentation
by: Xu, Fan, et al.
Published: (2025)