Cover Image

Structure-Attribute Transformations with Markov Chain Boost Graph Domain Adaptation

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Liu, Zhen, Zhang, Yongtao, Ren, Shaobo, You, Yuxin
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

Large Language Models Meet Graph Neural Networks: A Perspective of Graph Mining
by: You, Yuxin, et al.
Published: (2024)

On the Benefits of Attribute-Driven Graph Domain Adaptation
by: Fang, Ruiyi, et al.
Published: (2025)

PyGDA: A Python Library for Graph Domain Adaptation
by: Zhang, Zhen, et al.
Published: (2025)

Towards Unsupervised Open-Set Graph Domain Adaptation via Dual Reprogramming
by: Zhang, Zhen, et al.
Published: (2025)

Aggregate to Adapt: Node-Centric Aggregation for Multi-Source-Free Graph Domain Adaptation
by: Zhang, Zhen, et al.
Published: (2025)

Rethinking Propagation for Unsupervised Graph Domain Adaptation
by: Liu, Meihan, et al.
Published: (2024)

Revisiting, Benchmarking and Understanding Unsupervised Graph Domain Adaptation
by: Liu, Meihan, et al.
Published: (2024)

Learning Structure-Semantic Evolution Trajectories for Graph Domain Adaptation
by: Chen, Wei, et al.
Published: (2026)

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

DSBD: Dual-Aligned Structural Basis Distillation for Graph Domain Adaptation
by: Wang, Yingxu, et al.
Published: (2026)

USBD: Universal Structural Basis Distillation for Source-Free Graph Domain Adaptation
by: Wang, Yingxu, et al.
Published: (2026)

Gradual Domain Adaptation for Graph Learning
by: Lei, Pui Ieng, et al.
Published: (2025)

DisRFM: Polar Riemannian Flow Matching for Structure-Preserving Graph Domain Adaptation
by: Wang, Yingxu, et al.
Published: (2026)

Pairwise Alignment Improves Graph Domain Adaptation
by: Liu, Shikun, et al.
Published: (2024)

Geometric Understanding of Discriminability and Transferability for Visual Domain Adaptation
by: Luo, You-Wei, et al.
Published: (2024)

When Structure Doesn't Help: LLMs Do Not Read Text-Attributed Graphs as Effectively as We Expected
by: Xu, Haotian, et al.
Published: (2025)

Learning Attributed Graphlets: Predictive Graph Mining by Graphlets with Trainable Attribute
by: Shinji, Tajima, et al.
Published: (2024)

Graph Fourier Transformer with Structure-Frequency Information
by: Zhai, Yonghui, et al.
Published: (2025)

Rethinking Graph Domain Adaptation: A Spectral Contrastive Perspective
by: Zhang, Haoyu, et al.
Published: (2025)

Learning Extrapolative Sequence Transformations from Markov Chains
by: Hager, Sophia, et al.
Published: (2025)

Automatic Domain Adaptation by Transformers in In-Context Learning
by: Hataya, Ryuichiro, et al.
Published: (2024)

COD: Learning Conditional Invariant Representation for Domain Adaptation Regression
by: Yang, Hao-Ran, et al.
Published: (2024)

Multi-source Unsupervised Domain Adaptation on Graphs with Transferability Modeling
by: Zhao, Tianxiang, et al.
Published: (2024)

Applying Hybrid Graph Neural Networks to Strengthen Credit Risk Analysis
by: Sun, Mengfang, et al.
Published: (2024)

Reinforced Domain Selection for Continuous Domain Adaptation
by: Liu, Hanbing, et al.
Published: (2025)

Sparse Causal Discovery with Generative Intervention for Unsupervised Graph Domain Adaptation
by: Luo, Junyu, et al.
Published: (2025)

Attention with Markov: A Framework for Principled Analysis of Transformers via Markov Chains
by: Makkuva, Ashok Vardhan, et al.
Published: (2024)

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

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

Attributed Graph Clustering in Collaborative Settings
by: Zhang, Rui, et al.
Published: (2024)

GCL-OT: Graph Contrastive Learning with Optimal Transport for Heterophilic Text-Attributed Graphs
by: Ren, Yating, et al.
Published: (2025)

Graph Embedding in the Graph Fractional Fourier Transform Domain
by: Sheng, Changjie, et al.
Published: (2025)

Large Language Models as Topological Structure Enhancers for Text-Attributed Graphs
by: Sun, Shengyin, et al.
Published: (2023)

Distances for Markov Chains, and Their Differentiation
by: Brugère, Tristan, et al.
Published: (2023)

GraphShaper: Geometry-aware Alignment for Improving Transfer Learning in Text-Attributed Graphs
by: Zhang, Heng, et al.
Published: (2025)

GraphSB: Boosting Imbalanced Node Classification on Graphs through Structural Balance
by: Wang, Zhixiao, et al.
Published: (2026)

Safe-Subspace Pseudo-Label Refinement for Source-Free Graph Domain Adaptation
by: Wang, Yingxu, et al.
Published: (2026)

UniGraph: Learning a Unified Cross-Domain Foundation Model for Text-Attributed Graphs
by: He, Yufei, et al.
Published: (2024)

Structural Alignment Improves Graph Test-Time Adaptation
by: Hsu, Hans Hao-Hsun, et al.
Published: (2025)

Graph of Records: Boosting Retrieval Augmented Generation for Long-context Summarization with Graphs
by: Zhang, Haozhen, et al.
Published: (2024)