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Papers matching “graph structure learning” 63

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What Do Temporal Graph Learning Models Learn?
2025 arXiv (Cornell University) preprint Computer Science Advanced Graph Neural Networks Open access

Abigail J. Hayes, Tobias Schumacher, Markus Strohmaier

4

citations
Graph Learning Should Move Beyond Restrictive Views of Spectral and Message-Passing GNNs
2026 arXiv (Cornell University) preprint Computer Science Advanced Graph Neural Networks Open access

Antonis Vasileiou, Juan Cerviño, Pascal Frossard, Charilaos I. Kanatsoulis, Christopher Morris, Michael T. Schaub, +4 more

1

citations
Graph neural networks for the prediction of molecular structure-property relationships
2022 arXiv (Cornell University) preprint Computer Science Computational Drug Discovery Methods Open access

Jan G. Rittig, Qinghe Gao, Manuel Dahmen, Alexander Mitsos, Artur M. Schweidtmann

2

citations
Utilizing protein structure graph embeddings to predict the pathogenicity of missense variants
2024 bioRxiv (Cold Spring Harbor Laboratory) preprint Biochemistry, Genetics and Molecular Biology Genomics and Rare Diseases Open access

Martin Danner, Matthias Begemann, Miriam Elbracht, Ingo Kurth, Jeremias Krause

0

citations
Graph Neural Network-Based Multi-Agent Reinforcement Learning for Active Voltage Control: Performance and Topology Robustness
2025 SSRN Electronic Journal preprint Engineering Optimal Power Flow Distribution Open access

Chijioke Eze, Chetan Prakash, Antonello Monti

0

citations
DrugEx v3: Scaffold-Constrained Drug Design with Graph Transformer-based Reinforcement Learning
2021 ChemRxiv preprint Computer Science Computational Drug Discovery Methods Open access

Xuhan Liu, Kai Ye, Herman van Vlijmen, Adriaan P. IJzerman, Gerard J. P. van Westen

11

citations
Advancing Federated Learning in 6G: A Trusted Architecture with Graph-based Analysis
2023 arXiv (Cornell University) preprint Computer Science Privacy-Preserving Technologies in Data Open access

Wenxuan Ye, Chendi Qian, Xueli An, Xueqiang Yan, Georg Carle

0

citations
MultiGML: Multimodal Graph Machine Learning for Prediction of Adverse Drug Events
2022 bioRxiv (Cold Spring Harbor Laboratory) preprint Computer Science Computational Drug Discovery Methods Open access

Sophia Krix, Lauren Nicole DeLong, Sumit Madan, Daniel Domingo‐Fernándéz, Ashar Ahmad, Sheraz Gul, +2 more

3

citations
GraIP: A Benchmarking Framework For Neural Graph Inverse Problems
2026 arXiv (Cornell University) preprint Computer Science Advanced Graph Neural Networks Open access

Semih Cantürk, Andrei Manolache, Arman Mielke, Chendi Qian, Antoine Siraudin, Christopher Morris, +2 more

0

citations
Catch Me If You Can: Semi-supervised Graph Learning for Spotting Money Laundering
2023 arXiv (Cornell University) preprint Social Sciences Crime, Illicit Activities, and Governance Open access

Md Rezaul Karim, Felix Hermsen, Sisay Adugna Chala, Paola de Perthuis, Avikarsha Mandal

2

citations
Learning General Policies with Policy Gradient Methods
2025 arXiv (Cornell University) preprint Computer Science Reinforcement Learning in Robotics Open access

Simon Ståhlberg, Blai Bonet, Héctor Geffner

0

citations
Learning General Policies with Policy Gradient Methods
2025 arXiv (Cornell University) preprint Computer Science Reinforcement Learning in Robotics Open access

Simon Ståhlberg, Blai Bonet, Héctor Geffner

0

citations
Graph Neural Networks for Prediction of Fuel Ignition Quality
2020 ChemRxiv preprint Materials Science Machine Learning in Materials Science Open access

Artur M. Schweidtmann, Jan G. Rittig, Andrea Anna König, Martin Grohe, Alexander Mitsos, Manuel Dahmen

1

citations
Hierarchical Reinforcement Learning with Targeted Causal Interventions
2025 arXiv (Cornell University) preprint Computer Science Reinforcement Learning in Robotics Open access

0

citations
KNOWLEDGE GRAPH CONSTRUCTION FROM MATERIALS SCIENCE LITERATURE USING LARGE LANGUAGE MODELS AND ADVANCED DATA PREPROCESSING
2026 ChemRxiv preprint Materials Science Machine Learning in Materials Science Open access

Nasrin Mohammadi, Max Dreger, Diego Collarana, Mohammad J. Eslamibidgoli, Kourosh Malek, Michael Hermann Eikerling

1

citations
One Model, Any CSP: Graph Neural Networks as Fast Global Search Heuristics for Constraint Satisfaction
2022 arXiv (Cornell University) preprint Computer Science Constraint Satisfaction and Optimization Open access

Jan Tönshoff, Berke Kisin, Jakob Lindner, Martin Grohe

1

citations
GTCN-G: A Residual Graph-Temporal Fusion Network for Imbalanced Intrusion Detection
2025 arXiv (Cornell University) preprint Computer Science Network Security and Intrusion Detection Open access

Tianxiang Xu, Zhichao Wen, Xinyu Zhao, Yan Li, Chang Liu

1

citations
Symmetries and Expressive Requirements for Learning General Policies
2024 arXiv (Cornell University) preprint Computer Science AI-based Problem Solving and Planning Open access

Dominik Drexler, Simon Ståhlberg, Blai Bonet, Héctor Geffner

0

citations
Molecular Machine Learning in Chemical Process Design
2025 JuSER (Forschungszentrum Jülich) preprint Materials Science Machine Learning in Materials Science Open access

Jan G. Rittig, Manuel Dahmen, Martin Grohe, Philippe Schwaller, Alexander Mitsos

0

citations
Solving Max-Cut to Global Optimality via Feasibility-Preserving Graph Neural Networks
2026 arXiv (Cornell University) preprint Mathematics Advanced Optimization Algorithms Research Open access

Hao Chen, Chendi Qian, Christopher Morris, Andrea Lodi, Can Li

2

citations
Efficient Lookahead Encoding and Abstracted Width for Learning General Policies in Classical Planning
2026 arXiv (Cornell University) preprint Computer Science AI-based Problem Solving and Planning Open access

Michael Aichmüller, Simon Ståhlberg, Martin Funkquist, Hector Geffner

1

citations
Deep Learning of Causal Structures in High Dimensions
2022 arXiv (Cornell University) preprint Computer Science Bayesian Modeling and Causal Inference Open access

Kai Lagemann, Christian Lagemann, Bernd Taschler, Sach Mukherjee

0

citations
TopoEmbedX: A General Framework for Representation Learning on Topological Domains
2026 arXiv (Cornell University) preprint Computer Science Topological and Geometric Data Analysis Open access

Florian Frantzen, Ibrahem ALJabea, Inês Bonacho dos Anjos Henriques-Cadby, Theodore Papamarkou, Mustafa Hajij, Michael T. Schaub

0

citations
REAP: Learning General Rearrangement Heuristics from Motion-Planner Feedback
2026 arXiv (Cornell University) preprint Computer Science AI-based Problem Solving and Planning Open access

Daniel Swoboda, Héctor Geffner

0

citations
Probabilistically Rewired Message-Passing Neural Networks
2023 arXiv (Cornell University) preprint Computer Science Advanced Graph Neural Networks Open access

Chendi Qian, Andrei Manolache, Zhe Zeng, Guy Van den Broeck, Mathias Niepert

4

citations