Cover Image

Out-of-Distribution Graph Models Merging

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Wang, Yidi, Qiao, Ziyue, Gu, Jiawei, Zheng, Xubin, Wang, Pengyang, Pei, Xiaobing, Luo, Xiao
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

SpectralGap: Graph-Level Out-of-Distribution Detection via Laplacian Eigenvalue Gaps
by: Gu, Jiawei, et al.
Published: (2025)

NeuBM: Mitigating Model Bias in Graph Neural Networks through Neutral Input Calibration
by: Gu, Jiawei, et al.
Published: (2025)

GCAL: Adapting Graph Models to Evolving Domain Shifts
by: Qiao, Ziyue, et al.
Published: (2025)

Gradient Short-Circuit: Efficient Out-of-Distribution Detection via Feature Intervention
by: Gu, Jiawei, et al.
Published: (2025)

Single-View Graph Contrastive Learning with Soft Neighborhood Awareness
by: Sun, Qingqiang, et al.
Published: (2024)

AHSG: Adversarial Attack on High-level Semantics in Graph Neural Networks
by: Yuan, Kai, et al.
Published: (2024)

IENE: Identifying and Extrapolating the Node Environment for Out-of-Distribution Generalization on Graphs
by: Yang, Haoran, et al.
Published: (2024)

Rethinking Graph Contrastive Learning through Relative Similarity Preservation
by: Ning, Zhiyuan, et al.
Published: (2025)

Towards Continuous Reuse of Graph Models via Holistic Memory Diversification
by: Qiao, Ziyue, et al.
Published: (2024)

PRAGA: Prototype-aware Graph Adaptive Aggregation for Spatial Multi-modal Omics Analysis
by: Huang, Xinlei, et al.
Published: (2024)

Disentangled Multi-span Evolutionary Network against Temporal Knowledge Graph Reasoning
by: Dong, Hao, et al.
Published: (2025)

Generalizing Graph Neural Networks on Out-Of-Distribution Graphs
by: Fan, Shaohua, et al.
Published: (2021)

Out-of-Distribution Generalization in Graph Foundation Models
by: Li, Haoyang, et al.
Published: (2026)

Semi-supervised Domain Adaptation in Graph Transfer Learning
by: Qiao, Ziyue, et al.
Published: (2023)

Black-box Gradient Attack on Graph Neural Networks: Deeper Insights in Graph-based Attack and Defense
by: Zhan, Haoxi, et al.
Published: (2021)

OOD-GraphLLM: Graph Large Language Model for Out-of-Distribution Generalized Drug Synergy Prediction
by: Wang, Xin, et al.
Published: (2026)

Multi-view Fake News Detection Model Based on Dynamic Hypergraph
by: Ye, Rongping, et al.
Published: (2024)

Train with Perturbation, Infer after Merging: A Two-Stage Framework for Continual Learning
by: Qiu, Haomiao, et al.
Published: (2025)

Graph Synthetic Out-of-Distribution Exposure with Large Language Models
by: Xu, Haoyan, et al.
Published: (2025)

Principled Out-of-Distribution Generalization via Simplicity
by: Ge, Jiawei, et al.
Published: (2025)

Graph Structure and Feature Extrapolation for Out-of-Distribution Generalization
by: Li, Xiner, et al.
Published: (2023)

FOOGD: Federated Collaboration for Both Out-of-distribution Generalization and Detection
by: Liao, Xinting, et al.
Published: (2024)

Subgraph Aggregation for Out-of-Distribution Generalization on Graphs
by: Liu, Bowen, et al.
Published: (2024)

EPA: Neural Collapse Inspired Robust Out-of-Distribution Detector
by: Zhang, Jiawei, et al.
Published: (2024)

DIVE: Subgraph Disagreement for Graph Out-of-Distribution Generalization
by: Sun, Xin, et al.
Published: (2024)

Distributionally Robust Graph Out-of-Distribution Recommendation via Diffusion Model
by: Zhao, Chu, et al.
Published: (2025)

Sparsity and Out-of-Distribution Generalization
by: Aaronson, Scott, et al.
Published: (2026)

Decoupled Graph Energy-based Model for Node Out-of-Distribution Detection on Heterophilic Graphs
by: Chen, Yuhan, et al.
Published: (2025)

Temporal Inductive Path Neural Network for Temporal Knowledge Graph Reasoning
by: Dong, Hao, et al.
Published: (2023)

Enhancing Distribution and Label Consistency for Graph Out-of-Distribution Generalization
by: Wang, Song, et al.
Published: (2025)

On the Out-of-Distribution Generalization of Self-Supervised Learning
by: Qiang, Wenwen, et al.
Published: (2025)

Evolving Graph Learning for Out-of-Distribution Generalization in Non-stationary Environments
by: Sun, Qingyun, et al.
Published: (2025)

Graph Learning under Distribution Shifts: A Comprehensive Survey on Domain Adaptation, Out-of-distribution, and Continual Learning
by: Wu, Man, et al.
Published: (2024)

Generative Risk Minimization for Out-of-Distribution Generalization on Graphs
by: Wang, Song, et al.
Published: (2025)

Unifying Unsupervised Graph-Level Anomaly Detection and Out-of-Distribution Detection: A Benchmark
by: Wang, Yili, et al.
Published: (2024)

GOLD: Graph Out-of-Distribution Detection via Implicit Adversarial Latent Generation
by: Wang, Danny, et al.
Published: (2025)

GPS: Graph Contrastive Learning via Multi-scale Augmented Views from Adversarial Pooling
by: Ju, Wei, et al.
Published: (2024)

A Survey of Deep Graph Learning under Distribution Shifts: from Graph Out-of-Distribution Generalization to Adaptation
by: Zhang, Kexin, et al.
Published: (2024)

GOODAT: Towards Test-time Graph Out-of-Distribution Detection
by: Wang, Luzhi, et al.
Published: (2024)

Invariant Graph Transformer for Out-of-Distribution Generalization
by: Liao, Tianyin, et al.
Published: (2025)