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Papers matching “graph learning” 101

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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

0

citations
Learning to Search and Searching to Learn for Generalization in Planning
2026 arXiv (Cornell University) preprint Computer Science Reinforcement Learning in Robotics Open access

Michael Aichmüller, Yannik Hesse, Hector Geffner

0

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 P. Schaub, +4 more

0

citations
Future Directions in the Theory of Graph Machine Learning
2024 arXiv (Cornell University) preprint Computer Science Advanced Graph Neural Networks Open access

Fabrizio Frasca, Nadav Dym, Haggai Maron, İsmail İlkan Ceylan, Ron Levie, Derek Lim, +3 more

0

citations
Graph Learning with 1D Convolutions on Random Walks.
2021 arXiv (Cornell University) preprint Computer Science Advanced Graph Neural Networks Open access

Jan Toenshoff, Martin Ritzert, Hinrikus Wolf, Martin Grohe

5

citations
Temporal Heterogeneous Graph Pretraining for Relational Deep Learning
2026 arXiv (Cornell University) preprint Computer Science Advanced Graph Neural Networks Open access

Yixin Peng, 金儿, Diego Collarana, Stefan Decker

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
Accurately Solving Physical Systems with Graph Learning
2020 arXiv (Cornell University) preprint Computer Science Computer Graphics and Visualization Techniques Open access

Tassilo Kugelstadt, Wojtek Pałubicki, Jan Bender, Sören Pirk, Dominik Ludewig Michels

4

citations
Towards Automated Self-Supervised Learning for Truly Unsupervised Graph Anomaly Detection
2025 arXiv (Cornell University) preprint Computer Science Advanced Graph Neural Networks Open access

Zhong Li, Yuhang Wang, Matthijs van Leeuwen

0

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
GraphBench: Next-generation graph learning benchmarking
2025 arXiv (Cornell University) preprint Computer Science Advanced Graph Neural Networks Open access

1

citations
HopfE: Knowledge Graph Representation Learning using Inverse Hopf Fibrations
2021 arXiv (Cornell University) preprint Computer Science Advanced Graph Neural Networks Open access

Anson Bastos, Kuldeep Singh, Abhishek Nadgeri, Saeedeh Shekarpour, Isaiah Onando Mulang, Johannes Hoffart

1

citations
Which Algorithms Can Graph Neural Networks Learn?
2026 arXiv (Cornell University) preprint Computer Science Advanced Graph Neural Networks Open access

Solveig Wittig, Antonis Vasileiou, Robert R. Nerem, Timo Stoll, Floris Geerts, Yusu Wang, +1 more

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
Weisfeiler and Leman go Machine Learning: The Story so far
2021 arXiv (Cornell University) preprint Computer Science Advanced Graph Neural Networks Open access

Yaron Lipman, Haggai Maron, Bastian Rieck, Nils M. Kriege, Martin Grohe, Matthias Fey, +1 more

27

citations
Multi-fidelity graph neural networks for predicting toluene/water partition coefficients
2024 ChemRxiv preprint Computer Science Computational Drug Discovery Methods Open access

Thomas Nevolianis, Jan G. Rittig, Alexander Mitsos, Kai O. Leonhard

5

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
Iteratively Learning Representations for Unseen Entities with Inter-Rule Correlations
2023 arXiv (Cornell University) preprint Computer Science Advanced Graph Neural Networks Open access

Zihan Wang, Kai Zhao, Yongquan He, Zhumin Chen, Pengjie Ren, Maarten de Rijke, +1 more

0

citations
Where Did the Gap Go? Reassessing the Long-Range Graph Benchmark
2023 arXiv (Cornell University) preprint Computer Science Advanced Graph Neural Networks Open access

Jan Tönshoff, Martin Ritzert, Eran Rosenbluth, Martin Grohe

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
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
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
Towards Foundational Models for Molecular Learning on Large-Scale Multi-Task Datasets
2023 Zenodo (CERN European Organization for Nuclear Research) preprint Computer Science Computational Drug Discovery Methods Open access

Dominique Beaini, Shenyang Huang, Joao Alex Cunha, Zhiyi Li, Gabriela Moisescu-Pareja, Oleksandr Dymov, +19 more

0

citations
Towards Foundational Models for Molecular Learning on Large-Scale Multi-Task Datasets (Ultra Large Dataset)
2023 Zenodo (CERN European Organization for Nuclear Research) preprint Computer Science Computational Drug Discovery Methods Open access

Dominique Beaini, Shenyang Huang, Joao Alex Cunha, Zhiyi Li, Gabriela Moisescu-Pareja, Oleksandr Dymov, +20 more

0

citations