Graph Neural Networks

Also known as GNN

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88 papers in the last four weeks, up 31% on the four weeks before. 0.5% of all new papers.

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CRPS-LAM: Probabilistic Regional Weather Forecasting with Continuous Ranked Probability Score
Oct 10, 2025Erik Larsson, Joel Oskarsson, Tomas Landelius +1Graph Neural Networks Ensemble Learning
Linköping University · ETH AI Center · SMHI & Linköping University
Fractional Heat Kernel for Semi-Supervised Graph Learning with Small Training Sample Size
Oct 6, 2025Farid Bozorgnia, Vyacheslav Kungurtsev, Shirali Kadyrov +1Graph-Based Semi-Supervised Learning Graph Diffusion
Toward Uncertainty-Aware and Generalizable Neural Decoding for Quantum LDPC Codes
Oct 5, 2025Xiangjun Mi, Frank MuellerOOD Generalization Uncertainty Quantification
North Carolina State University, Raleigh, NC 27695, USA
GraphIFE: Rethinking Graph Imbalance Node Classification via Invariant Learning
Sep 28, 2025Fanlong Zeng, Wensheng Gan, Kangjie Chen +1Class-Imbalanced Learning Graph Neural Networks
School of Intelligent Systems Science and Engineering, Jinan University, Zhuhai 519070, China · School of Cybersecurity, Tianjin University, Tianjin 300354, China · University of Illinois Chicago, Chicago, USA
Self-Improving Neural Pruning: A Graph Neural Network Framework for Scalable Mixed Bundle Pricing
Sep 26, 2025Liangyu Ding, Chenghan Wu, Guokai Li +1Graph Neural Networks Combinatorial Optimization
School of Data Science, The Chinese University of Hong Kong, Shenzhen, Guangdong, China
Tackling GNARLy Problems: Graph Neural Algorithmic Reasoning Reimagined through Reinforcement Learning
Sep 23, 2025Alex Schutz, Victor-Alexandru Darvariu, Efimia Panagiotaki +2Graph Neural Networks Reinforcement Learning
Oxford Robotics Institute, University of Oxford · Stateful Robotics
Learning Contact Dynamics through Touching: Action-conditional Graph Neural Networks for Robotic Peg Insertion
Sep 15, 2025Zongyao Yi, Joachim Hertzberg, Martin AtzmuellerGraph Neural Networks Contact-Rich Robotic Manipulation
German Research Center for Artificial Intelligence, DFKI Niedersachsen, Osnabrück, Germany · Osnabrück University, Institute of Computer Science, Osnabrück, Germany
Alternative Graph Neural Networks: Synergizing GEV Models and Deep Learning for Travel Mode Choice Modeling
Sep 8, 2025Yuqi Zhou, Zhanhong Cheng, Dingyi Zhuang +3Graph Neural Networks Discrete Choice Modeling
aDepartment of Urban and Regional Planning, University of Florida · dDepartment of Civil and Environmental Engineering, Massachusetts Institute of Technology · bCollege of Architecture, Texas A&M University +1
A Note on Graphon-Signal Analysis of Graph Neural Networks
Aug 25, 2025Levi Rauchwerger, Ron LevieGraph Neural Networks Message Passing Neural Networks
RF-Informed Graph Neural Networks for Accurate and Data-Efficient Circuit Performance Prediction
Aug 22, 2025Anahita Asadi, Leonid Popryho, Inna Partin-VaisbandNeural Surrogate Modeling Graph Neural Networks
Department of Electrical and Computer Engineering, University of Illinois Chicago, Chicago, IL 60607 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
Graph Alignment for Benchmarking Graph Neural Networks and Learning Positional Encodings
May 19, 2025Adrien Lagesse, Marc LelargeGraph Neural Networks Synthetic Benchmark Generation
INRIA, École Normale Supérieure - PSL, Paris, France.
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
Understanding and Mitigating Under-Confidence in GNNs from the Final Layer
May 16, 2025Jincheng Huang, Jie Xu, Xiaoshuang Shi +3Graph Neural Networks Uncertainty Calibration
School of Computer Science and Engineering, University of Electronic Science and Technology of China · Southeast University
Traffic Engineering in Large-scale Networks with Generalizable Graph Neural Networks
Mar 31, 2025Fangtong Zhou, Xiaorui Liu, Ruozhou Yu +1Graph Neural Networks Learning to Optimize
Department of Computer Science, North Carolina State University, Raleigh, NC, 27606, USA · School of Computing and Augmented Intelligence, Arizona State University, Tempe, AZ, 85287, USA
GenShin: Guiding Rational Liposome Design by Ranking Liposomal Protein Corona through a Docking-Pose-Free GNN
Mar 16, 2025Pingfei Zhu, Hongyi Liu, Xueyan Liu +2Graph Neural Networks Materials Science
Key Laboratory of symbolic Computation and Knowledge Engineering of ministry of education, Jilin University, Qianjin Street 2699, Changchun, Jilin Province, 130012, China · State Key Laboratory of Natural and Biomimetic Drugs, School of Pharmaceutical Sciences, Peking University, Xue Yuan Road 38, Beijing 100191, China
Reforge: Low-Latency Distributed GNN Serving with Selective Embedding Recomputation
Jan 15, 2025Geon-Woo Kim, Donghyun Kim, Jeongyoon Moon +5Efficient Neural Network Inference Graph Neural Networks
The University of Texas at Austin · Georgia Institute of Technology
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
Information propagation dynamics in Deep Graph Networks
Oct 14, 2024Alessio GravinaGraph Neural Networks Graph Representation Learning
University of Pisa Department of Computer Science
Revealing the Pitfalls and Re-Evaluating the Advancement of Heterophilic Graph Learning
Sep 9, 2024Sitao Luan, Qincheng Lu, Chenqing Hua +3Graph Neural Networks Node Classification
Mila - Quebec Artiﬁcial Intelligence Institute · 1McGill University
GREAT: A Graph Edge Attention Network for the Electric Vehicle Routing Problem with Asymmetric Costs
Aug 29, 2024Attila Lischka, Filip Rydin, Jiaming Wu +2Vehicle Routing Graph Neural Networks
Chalmers University of Technology · University of Gothenburg
SSP-GNN: Learning to Track via Bilevel Optimization
Jul 5, 2024Griffin Golias, Masa Nakura-Fan, Vitaly AblavskyGraph Neural Networks Visual Object Tracking
Applied Physics Laboratory University of Washington Seattle, WA 98105 USA · Paul G. Allen School of Computer Science University of Washington Seattle, WA 98105 USA
GENIE: Watermarking Graph Neural Networks for Link Prediction
Jun 7, 2024Venkata Sai Pranav Bachina, Aaryan Ajay Sharma, Ankit Gangwal +1Graph Neural Networks Robust Watermarking
IIIT Hyderabad, India
Graph Unitary Message Passing
Mar 17, 2024Haiquan Qiu, Quanming YaoGraph Neural Networks Message Passing Neural Networks
Department of Electrical Engineering, Tsinghua University · 2Beijing National Research Center for Information Science and Technology · 3State Key laboratory of Space Network and Communications
Teaching MLP More Graph Information: A Three-stage Multitask Knowledge Distillation Framework
Mar 2, 2024Junxian Li, Bin Shi, Erfei Cui +2Knowledge Distillation Graph Neural Networks
Xi’an Jiaotong University · Arizona State University, Tempe, USA · Tongji University, Shanghai, China
Point-Voxel Absorbing Graph Representation Learning for Event Stream based Recognition
Jun 8, 2023Yuxiang Zhang, Chengguo Yuan, Xiao Wang +2Event-Based Vision Graph Neural Networks
aSchool of Computer Science and Technology, Anhui University, Hefei 230601, China.

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CRPS-LAM: Probabilistic Regional Weather Forecasting with Continuous Ranked Probability Score

Erik Larsson, Joel Oskarsson, Tomas Landelius, Fredrik Lindsten

Linköping University · ETH AI Center · SMHI & Linköping University

Graph Neural Networks Ensemble Learning Probabilistic Forecasting Spatiotemporal Forecasting Weather Forecasting

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Limited-Area Models (LAMs) enable weather forecasting over regional domains at higher resolutions than what is computationally feasible for global models. At such high resolutions, machine learning approaches for weather prediction increasingly rely on ensemble methods to produce probabilistic forecasts. However, existing machine learning LAMs are not scalable due to relying on computationally costly diffusion models or inefficient graph neural networks. We tackle this by introducing a new hybrid CNN/GNN architecture, tailored to the LAM weather forecasting problem. Using this architecture, we construct the DET-LAM deterministic model, producing LAM forecasts both more efficiently and accurately than its graph-based competitor. We then tackle the ensemble forecasting problem, by using this architecture as a backbone for the generative model CRPS-LAM. CRPS-LAM is trained using a Continuous Ranked Probability Score (CRPS) objective, enabling efficient training and sampling in a single forward pass. This yields a speedup of

\approx \times 39

compared to diffusion-based baselines. We evaluate our approach on regional domains in northern Europe, demonstrating that CRPS-LAM produces skillful and well-calibrated forecasts across a range of atmospheric variables.