Cover Image

GCAL: Adapting Graph Models to Evolving Domain Shifts

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Qiao, Ziyue, Cai, Qianyi, Dong, Hao, Gu, Jiawei, Wang, Pengyang, Xiao, Meng, Luo, Xiao, Xiong, Hui
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

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

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

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

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

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

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

Out-of-Distribution Graph Models Merging
by: Wang, Yidi, et al.
Published: (2025)

GALA: Graph Diffusion-based Alignment with Jigsaw for Source-free Domain Adaptation
by: Luo, Junyu, et al.
Published: (2024)

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

Partial Domain Adaptation via Importance Sampling-based Shift Correction
by: Guo, Cheng-Jun, et al.
Published: (2025)

Correcting Noisy Multilabel Predictions: Modeling Label Noise through Latent Space Shifts
by: Huang, Weipeng, et al.
Published: (2025)

Collaborative Multi-Agent Reinforcement Learning for Automated Feature Transformation with Graph-Driven Path Optimization
by: Huang, Xiaohan, et al.
Published: (2025)

Comprehend, Divide, and Conquer: Feature Subspace Exploration via Multi-Agent Hierarchical Reinforcement Learning
by: Zhang, Weiliang, et al.
Published: (2025)

Make Graph Neural Networks Great Again: A Generic Integration Paradigm of Topology-Free Patterns for Traffic Speed Prediction
by: Zhou, Yicheng, et al.
Published: (2024)

Rank and Align: Towards Effective Source-free Graph Domain Adaptation
by: Luo, Junyu, et al.
Published: (2024)

Can Large Language Models Help Experimental Design for Causal Discovery?
by: Li, Junyi, et al.
Published: (2025)

Leveraging Invariant Principle for Heterophilic Graph Structure Distribution Shifts
by: Yang, Jinluan, et al.
Published: (2024)

Mitigating Domain Shift in Federated Learning via Intra- and Inter-Domain Prototypes
by: Le, Huy Q., et al.
Published: (2025)

Collaborate to Adapt: Source-Free Graph Domain Adaptation via Bi-directional Adaptation
by: Zhang, Zhen, et al.
Published: (2024)

Towards Data-Centric AI: A Comprehensive Survey of Traditional, Reinforcement, and Generative Approaches for Tabular Data Transformation
by: Wang, Dongjie, et al.
Published: (2025)

A Comprehensive Survey on Deep Graph Representation Learning
by: Ju, Wei, et al.
Published: (2023)

SA-GDA: Spectral Augmentation for Graph Domain Adaptation
by: Pang, Jinhui, et al.
Published: (2024)

Adapt under Attack and Domain Shift: Unified Adversarial Meta-Learning and Domain Adaptation for Robust Automatic Modulation Classification
by: Owfi, Ali, et al.
Published: (2025)

When Graph Neural Network Meets Causality: Opportunities, Methodologies and An Outlook
by: Jiang, Wenzhao, et al.
Published: (2023)

Graphs Generalization under Distribution Shifts
by: Tian, Qin, et al.
Published: (2024)

FastFT: Accelerating Reinforced Feature Transformation via Advanced Exploration Strategies
by: He, Tianqi, et al.
Published: (2025)

Angle Domain Guidance: Latent Diffusion Requires Rotation Rather Than Extrapolation
by: Jin, Cheng, et al.
Published: (2025)

CoCo: A Coupled Contrastive Framework for Unsupervised Domain Adaptive Graph Classification
by: Yin, Nan, et al.
Published: (2023)

Mitigating Unauthorized Speech Synthesis for Voice Protection
by: Zhang, Zhisheng, et al.
Published: (2024)

Optimizing the Unknown: Black Box Bayesian Optimization with Energy-Based Model and Reinforcement Learning
by: Miao, Ruiyao, et al.
Published: (2025)

Easy Samples Are All You Need: Self-Evolving LLMs via Data-Efficient Reinforcement Learning
by: Yu, Zhiyin, et al.
Published: (2026)

Clarifying Shampoo: Adapting Spectral Descent to Stochasticity and the Parameter Trajectory
by: Eschenhagen, Runa, et al.
Published: (2026)

Cluster-guided Contrastive Class-imbalanced Graph Classification
by: Ju, Wei, et al.
Published: (2024)

Empowering Domain-Specific Language Models with Graph-Oriented Databases: A Paradigm Shift in Performance and Model Maintenance
by: Di Pasquale, Ricardo, et al.
Published: (2024)

HybridoNet-Adapt: A Domain-Adapted Framework for Accurate Lithium-Ion Battery RUL Prediction
by: Tran, Khoa, et al.
Published: (2025)

Calibration of Time-Series Forecasting: Detecting and Adapting Context-Driven Distribution Shift
by: Chen, Mouxiang, et al.
Published: (2023)

PrimeKG-CL: A Continual Graph Learning Benchmark on Evolving Biomedical Knowledge Graphs
by: Radwan, Yousef A., et al.
Published: (2026)

LoRD: Adapting Differentiable Driving Policies to Distribution Shifts
by: Diehl, Christopher, et al.
Published: (2024)

Temporal Generalization Estimation in Evolving Graphs
by: Lu, Bin, et al.
Published: (2024)

CMKL: Modality-Aware Continual Learning for Evolving Biomedical Knowledge Graphs
by: Radwan, Yousef A., et al.
Published: (2026)