Image de couverture de livre

Graph Structure and Feature Extrapolation for Out-of-Distribution Generalization

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Li, Xiner, Gui, Shurui, Luo, Youzhi, Ji, Shuiwang
Format:	Preprint
Publié:	2023
Sujets:	Machine Learning
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Discovering Physics Laws of Dynamical Systems via Invariant Function Learning
par: Gui, Shurui, et autres
Publié: (2025)

Active Test-Time Adaptation: Theoretical Analyses and An Algorithm
par: Gui, Shurui, et autres
Publié: (2024)

A Hierarchical Language Model For Interpretable Graph Reasoning
par: Khurana, Sambhav, et autres
Publié: (2024)

Mitigating Spurious Correlations in LLMs via Causality-Aware Post-Training
par: Gui, Shurui, et autres
Publié: (2025)

Equivariance via Minimal Frame Averaging for More Symmetries and Efficiency
par: Lin, Yuchao, et autres
Publié: (2024)

FlowX: Towards Explainable Graph Neural Networks via Message Flows
par: Gui, Shurui, et autres
Publié: (2022)

Geometry Informed Tokenization of Molecules for Language Model Generation
par: Li, Xiner, et autres
Publié: (2024)

IENE: Identifying and Extrapolating the Node Environment for Out-of-Distribution Generalization on Graphs
par: Yang, Haoran, et autres
Publié: (2024)

Curriculum Reinforcement Learning from Easy to Hard Tasks Improves LLM Reasoning
par: Parashar, Shubham, et autres
Publié: (2025)

Language Models for Controllable DNA Sequence Design
par: Su, Xingyu, et autres
Publié: (2025)

QH9: A Quantum Hamiltonian Prediction Benchmark for QM9 Molecules
par: Yu, Haiyang, et autres
Publié: (2023)

Out-of-Distribution Generalization in Graph Foundation Models
par: Li, Haoyang, et autres
Publié: (2026)

Invariant Graph Transformer for Out-of-Distribution Generalization
par: Liao, Tianyin, et autres
Publié: (2025)

Subgraph Aggregation for Out-of-Distribution Generalization on Graphs
par: Liu, Bowen, et autres
Publié: (2024)

Evolving Graph Learning for Out-of-Distribution Generalization in Non-stationary Environments
par: Sun, Qingyun, et autres
Publié: (2025)

SEDGE: Structural Extrapolated Data Generation
par: Zhang, Kun, et autres
Publié: (2026)

Invariant Tokenization of Crystalline Materials for Language Model Enabled Generation
par: Yan, Keqiang, et autres
Publié: (2025)

Dynamic Search for Inference-Time Alignment in Diffusion Models
par: Li, Xiner, et autres
Publié: (2025)

Out-of-Distribution Graph Models Merging
par: Wang, Yidi, et autres
Publié: (2025)

Generative Risk Minimization for Out-of-Distribution Generalization on Graphs
par: Wang, Song, et autres
Publié: (2025)

Enhancing Distribution and Label Consistency for Graph Out-of-Distribution Generalization
par: Wang, Song, et autres
Publié: (2025)

A Survey of Deep Graph Learning under Distribution Shifts: from Graph Out-of-Distribution Generalization to Adaptation
par: Zhang, Kexin, et autres
Publié: (2024)

Structural Entropy Guided Unsupervised Graph Out-Of-Distribution Detection
par: Hou, Yue, et autres
Publié: (2025)

CGRL: Causal-Guided Representation Learning for Graph Out-of-Distribution Generalization
par: Lu, Bowen, et autres
Publié: (2026)

Out-of-Distribution Generalization on Graphs via Progressive Inference
par: Xu, Yiming, et autres
Publié: (2025)

Exploring Graph-Transformer Out-of-Distribution Generalization Abilities
par: Niv, Itay, et autres
Publié: (2025)

Generalizing Graph Neural Networks on Out-Of-Distribution Graphs
par: Fan, Shaohua, et autres
Publié: (2021)

Equivariant Graph Network Approximations of High-Degree Polynomials for Force Field Prediction
par: Xu, Zhao, et autres
Publié: (2024)

Eliminating Position Bias of Language Models: A Mechanistic Approach
par: Wang, Ziqi, et autres
Publié: (2024)

Rethinking Graph Out-Of-Distribution Generalization: A Learnable Random Walk Perspective
par: Sun, Henan, et autres
Publié: (2025)

Beyond Generalization: A Survey of Out-Of-Distribution Adaptation on Graphs
par: Liu, Shuhan, et autres
Publié: (2024)

Pruning Spurious Subgraphs for Graph Out-of-Distribution Generalization
par: Yao, Tianjun, et autres
Publié: (2025)

Out-of-Distribution Generalization in Time Series: A Survey
par: Wu, Xin, et autres
Publié: (2025)

Out-of-Distribution Detection on Graphs: A Survey
par: Cai, Tingyi, et autres
Publié: (2025)

Unifying Invariant and Variant Features for Graph Out-of-Distribution via Probability of Necessity and Sufficiency
par: Chen, Xuexin, et autres
Publié: (2024)

ERIS: An Energy-Guided Feature Disentanglement Framework for Out-of-Distribution Time Series Classification
par: Wu, Xin, et autres
Publié: (2025)

DIVE: Subgraph Disagreement for Graph Out-of-Distribution Generalization
par: Sun, Xin, et autres
Publié: (2024)

Reward-Guided Iterative Refinement in Diffusion Models at Test-Time with Applications to Protein and DNA Design
par: Uehara, Masatoshi, et autres
Publié: (2025)

Complete and Efficient Graph Transformers for Crystal Material Property Prediction
par: Yan, Keqiang, et autres
Publié: (2024)

The Risk of Federated Learning to Skew Fine-Tuning Features and Underperform Out-of-Distribution Robustness
par: Du, Mengyao, et autres
Publié: (2024)