Dynamic Graph Learning

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Overview

Dynamic graph learning studies networks whose connections, attributes, or both evolve, from timestamped interaction events to sequences of graph snapshots. Common approaches include temporal graph neural networks with memory, attention, or state-space models, alongside methods that learn changing graph structure, temporal representations, or causal patterns. They are used for tasks such as link and event prediction, anomaly detection, traffic forecasting, and analysis of brain or transaction networks. A central challenge is balancing responsiveness to new patterns with retention of useful history, while ensuring efficient, interpretable models are evaluated under realistic distribution shifts and negative-sampling protocols.

Latest papers

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124 papers12 papers in the last four weeks, up 33% on the four weeks before. 0.1% of all new papers.

  1. Spectral Braids: A Topological Descriptor for Dynamic Directed Networks

    Oct 27, 2026Mehmet Emin Aktas, Esra AkbasDynamic Graph LearningSpectral Methods

    School of Data Science and Analytics, Kennesaw State University, Kennesaw, GA, USA · Department of Computer Science, Georgia State University, Atlanta, GA, USA

  2. DISRL: Dual-Scale Incremental Semi-Supervised Reinforcement Learning for Dynamic Community Tracking

    Oct 21, 2026Tianming Zhang, Jinxu Wang, Yixuan Zhang +4Dynamic Graph LearningReinforcement Learning

    College of Computer Science and Software Engineering Zhejiang University of Technology Hangzhou, China · School of Computer Science The University of Sydney Sydney, Australia

  3. From Complex Histories to Simple Predictors: Predictive Dimension in Dynamic Graph Learning

    Oct 20, 2026Hantong Feng, Duxin Chen, Wenwu YuDynamic Graph LearningPredictive Representation Learning

    School of Cyber Science and Engineering, Southeast University. · School of Mathematics, Southeast University. · Frontiers Science Center for Mobile Information Communication and Security.

  4. An Analysis of Semantic and Spatio-Temporal Co-evolution for Edge Classification on Dynamic Text-Attributed Graphs

    Oct 19, 2026Tyler Bonnet, Marek ReiText-Attributed Graph LearningDynamic Graph Learning

    Imperial College London London, United Kingdom

  5. Spectral Adaptive Graph Transformer for Efficient and Scalable Traffic Forecasting

    Oct 18, 2026Amirhossein Ghaffari, Susanna Pirttikangas, Ekaterina GilmanSpatiotemporal ForecastingTraffic Flow Estimation

    Future Computing Group, University of Oulu, 90570 Oulu, Finland

  6. Learning Across Temporal Graph Representation Silos

    Oct 14, 2026Minwoo Yu, Young-guk HaDynamic Graph LearningTemporal KGs

    M. Yu and Y.-g. Ha are with Smart Computing Laboratory, Department of Computer Science & Engineering, Konkuk University, Seoul 05029, Republic of Korea.

  7. Dynamic Graph World Modelling: Learning Future Dynamics from Temporal Context

    Oct 14, 2026Bo Li, Yue Yang, Yujin Huang +6Dynamic Graph LearningWorld Model Learning

    School of Information and Communication Technology, Griffith University, Australia · Maincode, Australia · School of Computing and Information Systems, University of Melbourne, Australia +2

  8. Refined Topology-Pass Scheduling: Damped Trust-Region Compensation for Dynamic k-NN Graphs in SE(3)-Equivariant Structure Prediction

    Oct 13, 2026Jiankai Huang, Hanwen ShenProtein Structure Predictionk-Nearest Neighbors

  9. Chasing Label Shifters: A Change-Aware Framework for Dynamic Graph Node Classification

    Oct 13, 2026Junghoon Kim, Seungyoon Choi, Hyunsung Kim +1Dynamic Graph LearningTemporal GNNs

    KAIST

  10. DSR-Net: Learning Dynamic Skeletal Relations for 3D Human Pose Estimation

    Oct 10, 2026Fan Li, Jian Xiang, LinLin Xue +13D Human Pose EstimationDynamic Graph Learning

    School of Computer Science and Technology, Zhejiang University of Science and Technology, Liuxia, Hangzhou 310023, China

  11. Your Temporal Link Predictor Is Blind to Who Is Active: A Missing Factor That Transfers Across Models

    Oct 4, 2026Ji Zhang, Zixin Liu, Yiran Ding +3Temporal Link PredictionDynamic Graph Learning

    Tsinghua University

  12. Differentiable Koopman Operator for Contrastive Learning on Dynamic Graphs

    Oct 2, 2026Md Abrar Jahin, Taufikur Rahman Fuad, Md Rizwan ParvezDynamic Graph LearningGraph SSL

    University of Southern California · Islamic University of Technology · Qatar Computing Research Institute (QCRI)

  13. WorldGraph: Graph-Native World Modeling

    Sep 28, 2026Zezhong Ding, Yipeng Li, Xike XieWorld Model LearningWorld Models

    School of Artificial Intelligence and Data Science, University of Science and Technology of China (USTC) · Data Darkness Lab, Suzhou Institute for Advanced Research, USTC · School of Biomedical Engineering, USTC

  14. Efficient Dynamic Algorithms for Graph Neural Networks with Non-Linear Propagation

    Sep 26, 2026Kiarash Banihashem, MohammadTaghi Hajiaghayi, Mahdi JafariRaviz +2Graph Neural NetworksDynamic Graph Learning

    Google Research

  15. Transfer Learning for Edge Classification on Dynamic Text-Attributed Graphs

    Sep 26, 2026Tyler Bonnet, Marek ReiText-Attributed Graph LearningCross-Domain Transfer Learning

    Imperial College London London, United Kingdom

  16. Adaptive Interaction Graphs for Particle Simulation

    Sep 25, 2026Aiden ZhouPhysics-Based SimulationDynamic Graph Learning

    Yale University, New Haven, Connecticut, USA.

  17. Beyond Static Graph World Models: Learning Stochastic Latent Dynamics over Evolving Topologies

    Sep 23, 2026Alex Schutz, Nick Hawes, Victor-Alexandru DarvariuLatent Dynamics ModelingDynamic Graph Learning

    Oxford Robotics Institute University of Oxford

  18. CacheDyG: Decoupling Temporal Propagation for Efficient Dynamic Graph Learning

    Sep 22, 2026PinHeng Zong, Ye YuanTemporal GNNsTemporal Link Prediction

    College of Computer and Information Science, Southwest University, Chongqing, China

  19. Time-Aligned Evolving Concept Graphs for Scientific Relation Forecasting

    Sep 16, 2026Fred Sun, Jingze Wang, Minkun Xu +1AI-Assisted Scientific ResearchTemporal Link Prediction

    Center for Brain-Inspired Computing Research, Department of Precision Instrument, Tsinghua University, Beijing, China · Guangdong Institute of Intelligence Science and Technology, Zhuhai, China

  20. Budgeted Task-Aware Acquisition of Dynamic Networks

    Sep 5, 2026Zihe ZhouDynamic Graph Learning

    Department of Mechanical & Industrial Engineering, University of Toronto Toronto, Ontario, Canada

  21. Dynamic Heterogeneous Graph Representation Learning: A Survey

    Sep 4, 2026Huan Liu, Pengfei Jiao, Jie Yin +2Graph Representation LearningDynamic Graph Learning

    School of Cyberspace, Hangzhou Dianzi University, China · Discipline of Business Analytics, The University of Sydney, Australia · Zhejiang Provincial Key Laboratory for Sensitive Data Security Protection and Confidentiality Management, Hangzhou, China

  22. Statistical Feature Augmentation for Anomaly Detection in Dynamic Graphs

    Sep 2, 2026Philipp Schlinge, Jean-Luc Schnipper, Martin AtzmuellerTemporal GNNsData Augmentation

    Osnabrück University, 49074 Osnabrueck,Germany · German Research Centre for Artificial Intelligence (DFKI), 49084 Osnabrück, Germany

  23. Temporal Memory-Aware Online Test-Time Adaptation on Dynamic Graphs

    Aug 28, 2026Bo Li, Xin Zheng, Ming Jin +2Test-Time AdaptationContinual Test-Time Adaptation

    Griffith University, Gold Coast, Australia · RMIT University, Melbourne, Australia

  24. C-Unseen: Weak Signal Detection in Dynamic Temporal Knowledge Graphs via LLM Reasoning

    Aug 27, 2026Yassir Lairgi, Ludovic Moncla, Khalid Benabdeslem +2Temporal KGsAnomaly Detection

    INSA Lyon, CNRS, UCBL, LIRIS, UMR5205, 69621 Villeurbanne, France · GAUC, Lyon, France

  25. MDTE: Minority-Aware Diffusion over Temporal Edge Events for Imbalanced Node Classification

    Aug 25, 2026Zhou Zelong, Zhang Tianming, Yang Zhengyi +4Node ClassificationClass-Imbalanced Learning

    Zhejiang University of Technology Hangzhou, China · The University of Sydney Sydney, Australia · Vecton AI Australia

  26. Enhancing Distance-Based Graph Autoencoders with Structural Penalties for Dynamic Graph Embedding

    Aug 19, 2026Aleksandar Tomčić, Miloš Savić, Miloš RadovanovićGraph Neural NetworksDynamic Graph Learning

    Department of Mathematics and Informatics, Faculty of Sciences, University of Novi Sad, Serbia Trg Dositeja Obradovi´ca 4, 21000 Novi Sad, Serbia

  27. A Network-driven Framework for Public Event Forecasting via Dynamic Interaction Network Evolution

    Aug 16, 2026Jie Wei, Yue Liu, Xiaochuan Tang +3Dynamic Graph LearningTime Series Forecasting

    Chengdu University of Technology, Chengdu, 610000, China. · Chengdu Neusoft University, Chengdu, 610000, China. · Jilin University, Changchun, 130000, China.

  28. Social Graph Mamba: Forecasting Pedestrian Movements Based on Social Context

    Aug 11, 2026Hong-Son Nguyen, Yen-Chen LiuPedestrian Trajectory PredictionPedestrian Behavior Modeling

    Department of Mechanical Engineering, National Cheng Kung University, Tainan 70101, Taiwan

  29. VeinCast: Physics-Guided Dynamic Field Graphs with Graph-Conditioned Fusion for Global Medium-Range Weather Forecasting

    Aug 10, 2026Zhisheng Chen, Jinhan Li, Yuxuan Li +6Dynamic Graph LearningPhysics-Informed ML

    1Nanyang Technological University · 2Tsinghua University · 3Peking University +1

  30. A Structural Dynamics Graph World Model: Unified Modeling, Constrained Rollout, and Interpretable Calibration

    Aug 9, 2026Wei Wang, Yaosen Chen, Han Yang +5Streamflow ForecastingWorld Model Learning

    Sobey Media Intelligence Laboratory