Joël Mathys - RankMe

18 papers A* 1A 1Journal 12Unranked 4

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Beyond Interpolation: Extrapolative Reasoning with Reinforcement Learning and Graph Neural Networks. CoRR Niccolò Grillo, Andrea Toccaceli, Joël Mathys, Benjamin Estermann, Stefania Fresca, Roger Wattenhofer
2025	J	`jnl`	Learn to Jump: Adaptive Random Walks for Long-Range Propagation through Graph Hierarchies. CoRR Joël Mathys, Federico Errica
2025	J	`jnl`	Synthetic Data for Blood Vessel Network Extraction. CoRR Joël Mathys, Andreas Plesner, Jorel Elmiger, Roger Wattenhofer
2024	A*	`conf`	CoRe-GD: A Hierarchical Framework for Scalable Graph Visualization with GNNs. ICLR Florian Grötschla, Joël Mathys, Robert Veres, Roger Wattenhofer
2024	J	`jnl`	CoRe-GD: A Hierarchical Framework for Scalable Graph Visualization with GNNs. CoRR Florian Grötschla, Joël Mathys, Robert Veres, Roger Wattenhofer
2024	A	`conf`	GraphFSA: A Finite State Automaton Framework for Algorithmic Learning on Graphs. ECAI Florian Grötschla, Joël Mathys, Christoffer Raun, Roger Wattenhofer
2024	J	`jnl`	GraphFSA: A Finite State Automaton Framework for Algorithmic Learning on Graphs. CoRR Florian Grötschla, Joël Mathys, Christoffer Raun, Roger Wattenhofer
2023	—	`conf`	Abstract Visual Reasoning Enabled by Language. CVPR Workshops Giacomo Camposampiero, Loïc Houmard, Benjamin Estermann, Joël Mathys, Roger Wattenhofer
2023	J	`jnl`	Flood and Echo: Algorithmic Alignment of GNNs with Distributed Computing. CoRR Joël Mathys, Florian Grötschla, Kalyan Varma Nadimpalli, Roger Wattenhofer
2023	J	`jnl`	SALSA-CLRS: A Sparse and Scalable Benchmark for Algorithmic Reasoning. CoRR Julian Minder, Florian Grötschla, Joël Mathys, Roger Wattenhofer
2023	—	`conf`	SURF: A Generalization Benchmark for GNNs Predicting Fluid Dynamics. LoG Stefan Künzli, Florian Grötschla, Joël Mathys, Roger Wattenhofer
2023	J	`jnl`	SURF: A Generalization Benchmark for GNNs Predicting Fluid Dynamics. CoRR Stefan Künzli, Florian Grötschla, Joël Mathys, Roger Wattenhofer
2023	J	`jnl`	Traffic4cast at NeurIPS 2022 - Predict Dynamics along Graph Edges from Sparse Node Data: Whole City Traffic and ETA from Stationary Vehicle Detectors. CoRR Moritz Neun, Christian Eichenberger, Henry Martin, Markus Spanring, Rahul Siripurapu, Daniel Springer, Leyan Deng, Chenwang Wu, Defu Lian, Min Zhou, Martin Lumiste, Andrei Ilie, Xinhua Wu, Cheng Lyu, Qing-Long Lu, Vishal Mahajan, Yichao Lu, Jiezhang Li, Junjun Li, Yue-Jiao Gong, Florian Grötschla, Joël Mathys, Ye Wei, He Haitao, Hui Fang, Kevin Malm, Fei Tang, Michael Kopp, David P. Kreil, Sepp Hochreiter
2023	J	`jnl`	Visual Abstraction and Reasoning through Language. CoRR Giacomo Camposampiero, Loïc Houmard, Benjamin Estermann, Joël Mathys, Roger Wattenhofer
2022	—	`conf`	Decentralized Graph Processing for Reachability Queries. ADMA (1) Joël Mathys, Robin Fritsch, Roger Wattenhofer
2022	J	`jnl`	Hierarchical Graph Structures for Congestion and ETA Prediction. CoRR Florian Grötschla, Joël Mathys
2022	J	`jnl`	Learning Graph Algorithms With Recurrent Graph Neural Networks. CoRR Florian Grötschla, Joël Mathys, Roger Wattenhofer
2021	—	`conf`	Traffic4cast at NeurIPS 2022 – Predict Dynamics along Graph Edges from Sparse Node Data: Whole City Traffic and ETA from Stationary Vehicle Detectors. NeurIPS (Competition and Demos) Moritz Neun, Christian Eichenberger, Henry Martin, Markus Spanring, Rahul Siripurapu, Daniel Springer, Leyan Deng, Chenwang Wu, Defu Lian, Min Zhou, Martin Lumiste, Andrei Ilie, Xinhua Wu, Cheng Lyu, Qing-Long Lu, Vishal Mahajan, Yichao Lu, Jiezhang Li, Junjun Li, Yue-Jiao Gong, Florian Grötschla, Joël Mathys, Ye Wei, He Haitao, Hui Fang, Kevin Malm, Fei Tang, Michael Kopp, David P. Kreil, Sepp Hochreiter