Graph Representation Learning

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Graph representation learning studies how to turn relational data into useful representations while preserving information about connectivity, node and edge attributes, and sometimes time or geometry. Common approaches include message-passing graph neural networks, spectral and positional encodings, graph Transformers, and self-supervised methods such as contrastive learning and masked prediction. These representations support tasks including node classification, link prediction, graph comparison, clustering, and molecular or social prediction; newer work also explores higher-order structure and foundation models that transfer across graphs. A central challenge is balancing expressive, scalable models with reliable generalization across graph sizes, domains, feature types, and structural shifts, while establishing when graph structure helps beyond simpler baselines.

Latest papers

305 papers33 papers in the last four weeks, up 3% on the four weeks before. 0.2% of all new papers.

Distilling and Adapting: A Topology-Aware Framework for Zero-Shot Interaction Prediction in Multiplex Biological Networks
Feb 20, 2026Alana Deng, Sugitha Janarthanan, Yan Sun +2Link Prediction Graph Representation Learning
Department of Computer Science, Western University, London, ON, Canada · Department of Biochemistry, Western University, London, ON, Canada
Geometry-Induced Diffusion on Graphs: A Learnable Weighted Laplacian for Spectral GNNs
Feb 20, 2026Mia Zosso, Ali Hariri, Victor Kawasaki-Borruat +2Long-Range Graph Learning Graph Representation Learning
École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland · École Normale Supérieure – PSL, Paris, France
Causal Neighbourhood Learning for Invariant Graph Representations
Feb 20, 2026Simi Job, Xiaohui Tao, Taotao Cai +2Graph Representation Learning Causal Representation Learning
School of Science, Engineering and Digital Technologies, University of Southern Queensland, Australia. · School of Data Science, Lingnan University, Hong Kong.
COMBA: Cross Batch Aggregation for Learning Large Graphs with Context Gating State Space Models
Feb 19, 2026Jiajun Shen, Yufei Jin, Yi He +1Graph Representation Learning Graph Neural Networks
Florida Atlantic University · William & Mary
Probability-Invariant Random Walk Learning on Gyral Folding-Based Cortical Similarity Networks for Alzheimer's and Lewy Body Dementia Diagnosis
Feb 19, 2026Minheng Chen, Tong Chen, Chao Cao +4Alzheimer's Disease Classification Brain Network Analysis
Department of Computer Science and Engineering, University of Texas at Arlington, United States · School of Computing, University of Georgia, United States · Department of Psychiatry, University of Cambridge, United Kingdom +1
Beyond Message Passing: A Symbolic Alternative for Expressive and Interpretable Graph Learning
Feb 18, 2026Chuqin Geng, Li Zhang, Haolin Ye +5Graph Representation Learning GNN Explainability
School of Computer Science, McGill University, Montreal, Canada · Department of Computer Science, University of Toronto, Toronto, Canada
SparTa: Sparse Graphical Task Models from a Handful of Demonstrations
Feb 18, 2026Adrian Röfer, Nick Heppert, Abhinav ValadaRobot Learning Learning from Demonstration
University of Freiburg, Germany · Zuse School ELIZA
Linked Data Classification using Neurochaos Learning
Feb 18, 2026Pooja Honna, Ayush Patravali, Nithin Nagaraj +1Node Classification Graph Representation Learning
Complex Systems Programme National Institute of Advanced Studies (NIAS) IISc Campus, Bangalore 560 012, India
Edge-Local and Qubit-Efficient Quantum Graph Learning for the NISQ Era
Feb 17, 2026Armin Ahmadkhaniha, Jake DoliskaniGraph Representation Learning Quantum Neural Networks
Department of Computing and Software, McMaster University
UrbanVerse: Learning Urban Region Representation Across Cities and Tasks
Feb 17, 2026Fengze Sun, Egemen Tanin, Shanika Karunasekera +3Urban Representation Learning Geospatial Representation Learning
School of Computing and Information System, University of Melbourne, Melbourne, Australia · School of Computer Science and Engineering, University of New South Wales, Sydney, Australia
Random Wavelet Features for Graph Kernel Machines
Feb 17, 2026Valentin de Bassompierre, Jean-Charles Delvenne, Laurent JacquesGraph Representation Learning Graph Embedding
INMA/ICTEAM, UCLouvain, Belgium
Size-Transferability of Graph Transformers with Convolutional Positional Encodings
Feb 16, 2026Javier Porras-Valenzuela, Zhiyang Wang, Teresa Shang +2Graph Positional Encoding Graph Transformer
Department of Electrical and Systems Engineering, University of Pennsylvania, Philadelphia, PA, USA · Halıcıoğlu Data Science Institute, University of California San Diego, La Jolla, CA, USA
Plain Transformers are Surprisingly Powerful Link Predictors
Feb 2, 2026Quang Truong, Yu Song, Donald Loveland +4Transformer Graph Representation Learning
Department of Computer Science and Engineering, Michigan State University, East Lansing, MI, USA. · Snap Inc., Bellevue, WA, USA.
Through the PRISm: Importance-Aware Scene Graphs for Semantic Image Retrieval
Dec 20, 2025Dimitrios Georgoulopoulos, Nikolaos Chaidos, Angeliki Dimitriou +1Image Retrieval Graph-Based Retrieval
National Technical University of Athens Athens, Greece
KIGNet: Physics-Motivated Multi-Graph Representation Learning for Explainable Jet Tagging
Dec 8, 2025Md Raqibul Islam, Adrita Khan, Mir Sazzat Hossain +6Graph Representation Learning Jet Tagging
Center for Computational & Data Sciences, Independent University, Bangladesh, Dhaka-1229, Bangladesh · Department of Theoretical Physics, University of Dhaka, Dhaka-1000, Bangladesh · Department of Physical Sciences, Independent University, Bangladesh, Dhaka-1229, Bangladesh
Enhancing Graph Representations with Neighborhood-Contextualized Message-Passing
Nov 14, 2025Brian Godwin Lim, Galvin Brice Lim, Renzo Roel Tan +2Graph Neural Networks Graph Representation Learning
Nara Institute of Science and Technology, Kyoto University, and Ateneo de Manila University · UNI-President Information Philippines Corporation · Nara Institute of Science and Technology and Ateneo de Manila University +2
Graph Homomorphism Distortion: A structural (pseudo)-metric for attributed graphs
Nov 4, 2025Martin Carrasco, Olga Zaghen, Kavir Sumaraj +2Graph Representation Learning GNN Expressivity
AIDOS Group, University of Fribourg, Fribourg, Switzerland · AMLAB, University of Amsterdam, Amsterdam, Netherland
Structured Spectral Graph Representation Learning for Multi-label Abnormality Analysis from 3D CT Scans
Oct 12, 2025Theo Di Piazza, Carole Lazarus, Olivier Nempont +1Graph Neural Networks Graph Representation Learning
INSA Lyon, University of Lyon, CNRS, INSERM, CREATIS UMR 5220, U1294, Villeurbanne, France · Hospices Civil de Lyon, Lyon, France · Philips Clinical Informatics, Innovation Paris, France
Computationally-efficient Graph Modeling with Refined Graph Random Features
Oct 9, 2025Krzysztof Choromanski, Avinava Dubey, Arijit Sehanobish +1Graph Representation Learning Randomized Sketching
Google DeepMind, New York, NY, USA · Columbia University, New York, NY, USA · Google Research, Mountain View, CA, USA +2
Rotary Position Encodings for Graphs
Sep 26, 2025Isaac Reid, Arijit Sehanobish, Cederik Höfs +7Graph Positional Encoding Rotary Positional Embeddings
University of Cambridge · Google DeepMind · Independent Researcher +3
Hybrid Topic-Semantic Labeling and Graph Embeddings for Unsupervised Legal Document Clustering
Aug 31, 2025Deepak Bastola, Woohyeok ChoiText Clustering Legal Document Analysis
Department of Mathematical Sciences, Salisbury University · Department of Mathematics and Statistics, Carleton College
Graph Structure Learning with Temporal Graph Information Bottleneck for Inductive Representation Learning
Aug 20, 2025Jiafeng Xiong, Rizos SakellariouGraph Structure Learning Temporal GNNs
Department of Computer Science, University of Manchester, UK
Evaluating Out-of-Distribution Robustness in Graph-Based Android Malware Classification: A New Principled Benchmark
Aug 8, 2025Ngoc N. Tran, Anwar Said, Waseem Abbas +2Distribution Shift Robustness Graph Representation Learning
Vanderbilt University, USA · Highmark Health, USA · University of Texas at Dallas, USA
Learning Latent Graph Geometry via Fixed-Point Schrödinger-Type Activation: A Theoretical Study
Jul 27, 2025Dmitry Pasechnyuk-Vilensky, Martin TakáčGraph Structure Learning Graph Neural Networks
MBZUAI, UAE
A Machine Learning Benchmarking Framework for Lipid Nanoparticle Transfection Efficiency Prediction
Jul 3, 2025Asal Mehradfar, Mohammad Shahab Sepehri, Jose Miguel Hernandez-Lobato +4Graph Representation Learning Molecular Property Prediction
Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA · Department of Engineering, University of Cambridge, Cambridge, UK · Pharmaceutical Sciences Division, School of Pharmacy, University of Wisconsin-Madison, Madison, WI +1
Macro Graph of Experts for Billion-Scale Multi-Task Recommendation
Jun 12, 2025Hongyu Yao, Zijin Hong, Hao Chen +6Graph Representation Learning Multi-Task Learning
The Hong Kong Polytechnic University Hong Kong SAR, China · National University of Defense Technology Changsha, China · Beihang University Beijing, China
Efficient Learning of Balanced Signed Graphs via Sparse Linear Programming
Jun 2, 2025Haruki Yokota, Hiroshi Higashi, Yuichi Tanaka +1Graph Structure Learning Graph Representation Learning
Relation-Aware Graph Foundation Model
May 17, 2025Jianxiang Yu, Jiapeng Zhu, Yibo Zhao +4Graph Neural Networks Graph Representation Learning
School of Data Science and Engineering, East China Normal University · Ant Group
Causally Fair Node Classification on Non-IID Graph Data
May 3, 2025Yucong Dai, Lu Zhang, Yaowei Hu +2Structural Causal Models Graph Representation Learning
Clemson University · University of Arkansas · Walmart Inc.
MEGA: Message Passing Neural Networks for Multigraphs with EdGe Attributes
Nov 29, 2024H. Çağrı Bilgi, Kubilay AtasuGraph Neural Networks Graph Representation Learning
1Delft University of Technology

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Distilling and Adapting: A Topology-Aware Framework for Zero-Shot Interaction Prediction in Multiplex Biological Networks

Alana Deng, Sugitha Janarthanan, Yan Sun, Zihao Jing+1

Department of Computer Science, Western University, London, ON, Canada · Department of Biochemistry, Western University, London, ON, Canada

Link Prediction Graph Representation Learning Multimodal Graph Learning

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Multiplex Biological Networks (MBNs), which represent multiple interaction types between entities, are crucial for understanding complex biological systems. Yet, existing methods often inadequately model multiplexity, struggle to integrate structural and sequence information, and face difficulties in zero-shot prediction for unseen entities with no prior neighbourhood information. To address these limitations, we propose a novel framework for zero-shot interaction prediction in MBNs by leveraging context-aware representation learning and knowledge distillation. Our approach leverages domain-specific foundation models to generate enriched embeddings, introduces a topology-aware graph tokenizer to capture multiplexity and higher-order connectivity, and employs contrastive learning to align embeddings across modalities. A teacher-student distillation strategy further enables robust zero-shot generalization. Experimental results demonstrate that our framework outperforms state-of-the-art methods in interaction prediction for MBNs, providing a powerful tool for exploring various biological interactions and advancing personalized therapeutics.