Improving Graph Out-of-distribution Generalization Beyond Causality
Fuente:
arXiv
Saved in:
| Main Authors: | Xu, Can, Cheng, Yao, Yu, Jianxiang, Wang, Haosen, Lv, Jingsong, Liu, Yao, Li, Xiang |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Boosting Graph Foundation Model from Structural Perspective
by: Cheng, Yao, et al.
Published: (2024)
by: Cheng, Yao, et al.
Published: (2024)
A Survey on Learning from Graphs with Heterophily: Recent Advances and Future Directions
by: Gong, Chenghua, et al.
Published: (2024)
by: Gong, Chenghua, et al.
Published: (2024)
Self-Pro: A Self-Prompt and Tuning Framework for Graph Neural Networks
by: Gong, Chenghua, et al.
Published: (2023)
by: Gong, Chenghua, et al.
Published: (2023)
Variational Graph Autoencoder for Heterogeneous Information Networks with Missing and Inaccurate Attributes
by: Zhao, Yige, et al.
Published: (2023)
by: Zhao, Yige, et al.
Published: (2023)
Graph Synthetic Out-of-Distribution Exposure with Large Language Models
by: Xu, Haoyan, et al.
Published: (2025)
by: Xu, Haoyan, et al.
Published: (2025)
Homophily-aware Heterogeneous Graph Contrastive Learning
by: Wang, Haosen, et al.
Published: (2025)
by: Wang, Haosen, et al.
Published: (2025)
Bounded and Uniform Energy-based Out-of-distribution Detection for Graphs
by: Yang, Shenzhi, et al.
Published: (2025)
by: Yang, Shenzhi, et al.
Published: (2025)
Heterogeneous Graph Contrastive Learning with Meta-path Contexts and Adaptively Weighted Negative Samples
by: Yu, Jianxiang, et al.
Published: (2022)
by: Yu, Jianxiang, et al.
Published: (2022)
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)
Negative as Positive: Enhancing Out-of-distribution Generalization for Graph Contrastive Learning
by: Wang, Zixu, et al.
Published: (2024)
by: Wang, Zixu, et al.
Published: (2024)
Geometric-Facilitated Denoising Diffusion Model for 3D Molecule Generation
by: Xu, Can, et al.
Published: (2024)
by: Xu, Can, et al.
Published: (2024)
CGRL: Causal-Guided Representation Learning for Graph Out-of-Distribution Generalization
by: Lu, Bowen, et al.
Published: (2026)
by: Lu, Bowen, et al.
Published: (2026)
Relation-Aware Graph Foundation Model
by: Yu, Jianxiang, et al.
Published: (2025)
by: Yu, Jianxiang, et al.
Published: (2025)
Leveraging Large Language Models for Node Generation in Few-Shot Learning on Text-Attributed Graphs
by: Yu, Jianxiang, et al.
Published: (2023)
by: Yu, Jianxiang, et al.
Published: (2023)
OOD-GraphLLM: Graph Large Language Model for Out-of-Distribution Generalized Drug Synergy Prediction
by: Wang, Xin, et al.
Published: (2026)
by: Wang, Xin, et al.
Published: (2026)
GQWformer: A Quantum-based Transformer for Graph Representation Learning
by: Yu, Lei, et al.
Published: (2024)
by: Yu, Lei, et al.
Published: (2024)
Few-Shot Causal Representation Learning for Out-of-Distribution Generalization on Heterogeneous Graphs
by: Ding, Pengfei, et al.
Published: (2024)
by: Ding, Pengfei, et al.
Published: (2024)
Pruning Spurious Subgraphs for Graph Out-of-Distribution Generalization
by: Yao, Tianjun, et al.
Published: (2025)
by: Yao, Tianjun, et al.
Published: (2025)
Hierarchical Vector Quantized Graph Autoencoder with Annealing-Based Code Selection
by: Zeng, Long, et al.
Published: (2025)
by: Zeng, Long, et al.
Published: (2025)
Bridging Multicalibration and Out-of-distribution Generalization Beyond Covariate Shift
by: Wu, Jiayun, et al.
Published: (2024)
by: Wu, Jiayun, et al.
Published: (2024)
A Survey of Out-of-distribution Generalization for Graph Machine Learning from a Causal View
by: Ma, Jing
Published: (2024)
by: Ma, Jing
Published: (2024)
Spurious Feature Diversification Improves Out-of-distribution Generalization
by: Lin, Yong, et al.
Published: (2023)
by: Lin, Yong, et al.
Published: (2023)
FOOGD: Federated Collaboration for Both Out-of-distribution Generalization and Detection
by: Liao, Xinting, et al.
Published: (2024)
by: Liao, Xinting, 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)
Uncovering Causal Relation Shifts in Event Sequences under Out-of-Domain Interventions
by: Zinat, Kazi Tasnim, et al.
Published: (2025)
by: Zinat, Kazi Tasnim, et al.
Published: (2025)
Graph Out-of-Distribution Generalization via Causal Intervention
by: Wu, Qitian, et al.
Published: (2024)
by: Wu, Qitian, et al.
Published: (2024)
Few-Shot Graph Out-of-Distribution Detection with LLMs
by: Xu, Haoyan, et al.
Published: (2025)
by: Xu, Haoyan, et al.
Published: (2025)
RELIEF: Reinforcement Learning Empowered Graph Feature Prompt Tuning
by: Zhu, Jiapeng, et al.
Published: (2024)
by: Zhu, Jiapeng, et al.
Published: (2024)
Human Cognition Inspired RAG with Knowledge Graph for Complex Problem Solving
by: Cheng, Yao, et al.
Published: (2025)
by: Cheng, Yao, et al.
Published: (2025)
Generative models for decision-making under distributional shift
by: Cheng, Xiuyuan, et al.
Published: (2026)
by: Cheng, Xiuyuan, et al.
Published: (2026)
Neuron Activation Coverage: Rethinking Out-of-distribution Detection and Generalization
by: Liu, Yibing, et al.
Published: (2023)
by: Liu, Yibing, et al.
Published: (2023)
Causality-Inspired Safe Residual Correction for Multivariate Time Series
by: Xie, Jianxiang, et al.
Published: (2025)
by: Xie, Jianxiang, 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)
Out-of-Distribution Generalization in Graph Foundation Models
by: Li, Haoyang, et al.
Published: (2026)
by: Li, Haoyang, et al.
Published: (2026)
Out-of-Distribution Generalization on Graphs via Progressive Inference
by: Xu, Yiming, et al.
Published: (2025)
by: Xu, Yiming, et al.
Published: (2025)
Regularized Multi-LLMs Collaboration for Enhanced Score-based Causal Discovery
by: Li, Xiaoxuan, et al.
Published: (2024)
by: Li, Xiaoxuan, et al.
Published: (2024)
Improving Out-of-Distribution Generalization of Trajectory Prediction for Autonomous Driving via Polynomial Representations
by: Yao, Yue, et al.
Published: (2024)
by: Yao, Yue, et al.
Published: (2024)
Causal Graph Discovery with Retrieval-Augmented Generation based Large Language Models
by: Zhang, Yuzhe, et al.
Published: (2024)
by: Zhang, Yuzhe, et al.
Published: (2024)
Disentangled Graph Prompting for Out-Of-Distribution Detection
by: Yang, Cheng, et al.
Published: (2026)
by: Yang, Cheng, et al.
Published: (2026)
Transferable Graph Condensation from the Causal Perspective
by: Du, Huaming, et al.
Published: (2026)
by: Du, Huaming, et al.
Published: (2026)
Similar Items
-
Boosting Graph Foundation Model from Structural Perspective
by: Cheng, Yao, et al.
Published: (2024) -
A Survey on Learning from Graphs with Heterophily: Recent Advances and Future Directions
by: Gong, Chenghua, et al.
Published: (2024) -
Self-Pro: A Self-Prompt and Tuning Framework for Graph Neural Networks
by: Gong, Chenghua, et al.
Published: (2023) -
Variational Graph Autoencoder for Heterogeneous Information Networks with Missing and Inaccurate Attributes
by: Zhao, Yige, et al.
Published: (2023) -
Graph Synthetic Out-of-Distribution Exposure with Large Language Models
by: Xu, Haoyan, et al.
Published: (2025)