Graph Structure Learning

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Overview

Graph structure learning studies how to infer or refine edges, weights, and higher-order connections when the network is unknown, noisy, changing, or poorly matched to a task. Methods range from sparse precision-matrix and Laplacian estimation and score-based directed acyclic graph learning to similarity-based construction, attention-driven rewiring, and task-aware bilevel optimization. Learned structures support tasks such as node classification, link prediction, time-series forecasting, recommendation, and biomedical analysis, including settings with scarce labels, multimodal features, or evolving relationships. A central tension is whether a graph should faithfully recover underlying dependencies or maximize downstream performance: task-driven rewiring can help prediction but may overfit, weaken interpretability, or fail to transfer across datasets.

Latest papers

CardsList

139 papers14 papers in the last four weeks, up 8% on the four weeks before. 0.1% of all new papers.

  1. UCVE: Graph Structured Retrieval for Compliance Validation

    Oct 27, 2026Emily Chen, Michelle Menachery, Himanshu Kumar +2Graph-Based RetrievalAI Regulatory Compliance

    Capital One, AI Foundations

  2. Spatially-Aware Self-Organizing Graph Autoencoders via Localized Hebbian Learning

    Oct 25, 2026Robin Koç, Hazal Moğultay Özcan, Fatoş T. Yarman VuralVisual Representation LearningConvolutional Autoencoder

    Computer Engineering Department, Middle East Technical University, Ankara, Türkiye

  3. DualGSL: Prior-Guided Graph Structure Learning with Node-Adaptive Prediction Fusion

    Oct 23, 2026Yuxia Sun, Yutszyuk Wong, Huihong Chen +3Graph Structure LearningNode Classification

    the College of Information Science and Technology, Jinan University, Guangzhou 510632, China · Jinan University, Guangzhou 510632, China · Sun Yat-sen University +1

  4. Beyond Phenotypic Similarity: Relation Refinement and Selective Population Graph Learning for Multimodal Brain Disorder Diagnosis

    Oct 22, 2026Yinyu LanBrain Disorder ClassificationMultimodal Graph Learning

    School of Medicine and Health, Harbin Institute of Technology, Harbin 150001, China

  5. Robust Latent Variable Graphical Models: Exact Recovery and Fundamental Limits

    Oct 19, 2026Chuansen Peng, Xiaojing ShenRobust EstimationGraph Structure Learning

    School of Mathematics, Sichuan University, Chengdu 610064, China

  6. Student Copula Markov Networks

    Oct 13, 2026Salha Mamane, Cheikh Tidiane SeckProbabilistic Graphical ModelsGraph Structure Learning

    School of Statistics and Actuarial Science, University of the Witwatersrand · Department of Mathematics, Alioune Diop University of Bambey

  7. Edge Accuracy Is Not Enough: Why Dynamics-Learned Structure Fails to Transfer to Inverse Problems

    Oct 7, 2026Nicholas Tan Jerome, Fangnian WangInverse ProblemsGraph Structure Learning

    Institute for Data Processing and Electronics (IPE) Karlsruhe Institute of Technology (KIT) Karlsruhe, Germany · Institute for Thermal Energy Technology and Safety (ITES) Karlsruhe Institute of Technology (KIT) Karlsruhe, Germany

  8. LFHE: Local-First Heuristic Evolution for Bounded Local Topology Search in Decentralized Learning with Non-IID Data

    Oct 6, 2026Yin-Kuan Liang, Yan Gao, Yang LongGraph Structure LearningDecentralized Learning

    Durham University · University of Cambridge

  9. Joint Precision Neural Networks: Task-Aware Dependency and Predictive Learning

    Oct 5, 2026Andrea Cavallo, Samuel Rey, Antonio G. Marques +1Graph Structure LearningGraph Neural Networks

    INSY Department, Delft University of Technology · Department of Signal Theory and Communications, King Juan Carlos University

  10. Hold-Out Scoring for Efficient Gaussian DAG Learning

    Oct 2, 2026Donguk Shin, Byeongguk Kang, Inseol Lee +1Graph Structure LearningCausal Structure Learning

    Department of Statistics, Seoul National University. · Interdisciplinary Program in Artificial Intelligence, Seoul National University. · Institute for Data Innovation in Science, Seoul National University.

  11. No-Free-Graph: Learning When Multimodal Data Should Be Graphified

    Oct 2, 2026Zekai Chen, Kai Hu, YuXin Zeng +6Multimodal Graph LearningGraph Structure Learning

    Beijing Institute of Technology · Sun Yat-sen University · Shandong University

  12. World-as-Graph: Relational World Modeling Through Latent Space Graphs

    Sep 30, 2026Yaqi Yang, Shuo Huang, Yujin Huang +3Graph Structure LearningWorld Model Learning

    School of Computing Technologies, RMIT University, Australia · Faculty of Information Technology, Monash University, Australia · KStelrix Star Dynamics Lab, KStelrix, China +1

  13. GARDiff: Graph-Aligned Residual Diffusion for Probabilistic Multivariate Time-Series Forecasting

    Sep 29, 2026Rui Han, Min Yang, Xu Zhang +3Multivariate Time Series ForecastingGraph Structure Learning

    Shandong University, Jinan, China · Macquarie University, Sydney, Australia · China University of Petroleum (East China), Qingdao, China +1

  14. Learning the Structure of Triangular Transport Maps

    Sep 29, 2026Morten Blørstad, Pekka Parviainen, Berent Ånund Strømnes LundeFlow Map LearningDensity Estimation

    Department of Informatics, University of Bergen · Equinor

  15. When Trees Are Not Enough: Learning Mixed-Topology Feature Graphs with Adaptive Graph Sparse Autoencoders

    Sep 28, 2026Xiaozuo Shen, Yifei Cai, Tian Tan +3Sparse AutoencodersMechanistic Interpretability

    University of Arizona · Iowa State University · Old Dominion University

  16. Non-Adaptive Learning of Sparse Erdős--Rényi Graphs via Affine Splitting

    Sep 27, 2026Hoang TaGraph Structure LearningSparse Recovery

    Department of Computer Science, Hanoi University of Science and Technology, Vietnam

  17. Learning the Graph and the Embedding Together: Classifier-Independent Rewiring for Heterophilic Node Classification

    Sep 26, 2026Harshit Kumar, Sujan Chakraborty, Priyanka Saha +2Graph RewiringGraph Structure Learning

    School of Data Science, Indian Institute of Science Education and Research Thiruvananthapuram, Thiruvananthapuram 695551, India

  18. Graph Learning with Spectral Connectivity Priors for Scarce Data

    Sep 23, 2026Mingxiao Liu, Bahar Oveisgharan, Bingyan Zou +3Graph Signal ProcessingGraph Structure Learning

    Tsinghua University, China · York University, Canada

  19. Fast Graph Laplacian Estimation using Effective Resistance

    Sep 20, 2026Christoffer Kjellson, Claudio Altafini, Emma TeglingGraph Structure LearningProbabilistic Graphical Models

    Department of Automatic Control, Lund University · ELLIIT Strategic Research Area · Division of Automatic Control, Department of Electrical Engineering, Linköping University

  20. GSLAD: Prototype-Regularized Graph Structure Learning for Multivariate Time Series Anomaly Detection

    Sep 14, 2026Zepeng Zhang, Fuad Khuri, Keivan Faghih Niresi +1Graph Structure LearningIndustrial Anomaly Detection

    Intelligent Maintenance and Operations Systems (IMOS) Lab École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland

  21. ABSOL: Aggregated Bayesian Subsampling Orchestrated with LLMs

    Sep 14, 2026Jackson Hassell, Chen Shen, Estevam HruschkaGraph Structure LearningBayesian Network Structure Learning

    Megagon Labs

  22. Tensor Network Moral Graph Recovery of Discrete Probability Distributions

    Sep 8, 2026Á. Troyano Olivas, Chi-Hang Fred Fung, Hans H. Brunner +2Tensor NetworksGraph Structure Learning

    Heisenberg Research Center (Munich), Huawei Technologies Duesseldorf GmbH, Germany · Center for Computational Simulation, Universidad Politécnica de Madrid, Madrid, Spain

  23. Bayesian Matrix-Valued Graphs for Context-Dependent Multivariate Relationships

    Sep 7, 2026Papri DeyGraph Structure LearningBayesian Inference

  24. Multi-granularity Adaptive Hypergraph Representation Learning via Granular-ball

    Sep 4, 2026Sen Zhao, Yifan Guan, Jinyuan Ni +6Hypergraph LearningHypergraph Neural Networks

    Chongqing University of Posts and Telecommunications

  25. MURAL: Multimodal Uncertainty-aware Recommendation via Adaptive edge Learning

    Sep 4, 2026Ahmad Mousavi, Majid Alikhani, Yeon-Chang Lee +2Multimodal RecommendationMultimodal Graph Learning

    Department of Mathematics and Statistics American University · Independent Researcher Toronto, Ontario, Canada · Independent Researcher +4

  26. Geometry-Aware Graph Construction via Adaptive Spectral Bandwidth Control

    Sep 3, 2026Ecem Bozkurt, Antonio OrtegaGraph Structure LearningGraph-Based Semi-Supervised Learning

    Department of Electrical and Computer Engineering University of Southern California, Los Angeles, CA, USA

  27. From topology learning to graph generation: A unifying perspective

    Sep 2, 2026Xiaowen Dong, Hoi-To Wai, Siheng Chen +2Graph Structure LearningGraph Generation

    University of Oxford · The Chinese University of Hong Kong · Shanghai Jiao Tong University +2

  28. Import What You Need: Learning When and How to Augment EHR Graphs with External Knowledge

    Sep 1, 2026Chen Chen, Mohsen Nayebi Kerdabadi, Dongjie Wang +2Graph Structure LearningLongitudinal EHR Modeling

    Electrical Engineering and Computer Science, University of Kansas, USA · Health Outcomes and Biomedical Informatics, University of Florida, USA

  29. Conservative Hybrid Graph Networks for Process Systems with Learned Routing

    Aug 28, 2026Paolo GuidaPhysics-Informed GNNsSystem Identification

    Physical Science and Engineering King Abdullah University of Science and Technology (KAUST) Thuwal, Saudi Arabia

  30. Decentralized Multitask Learning over Learned Task Graphs

    Aug 27, 2026Zirui Wan, Stefan VlaskiGraph Structure LearningMulti-Task Learning

    Department of Electrical and Electronic Engineering, Imperial College London, UK