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2020 – today
- 2024
[c7]Philip Jordan, Florian Grötschla, Flint Xiaofeng Fan, Roger Wattenhofer:
Decentralized Federated Policy Gradient with Byzantine Fault-Tolerance and Provably Fast Convergence. AAMAS 2024: 964-972- [c6]Florian Grötschla, Joël Mathys, Christoffer Raun, Roger Wattenhofer:
GraphFSA: A Finite State Automaton Framework for Algorithmic Learning on Graphs. ECAI 2024: 2935-2942 - [c5]Florian Grötschla, Joël Mathys, Robert Veres, Roger Wattenhofer:
CoRe-GD: A Hierarchical Framework for Scalable Graph Visualization with GNNs. ICLR 2024 - [c4]Florian Grötschla, Luca Strässle, Luca A. Lanzendörfer, Roger Wattenhofer:
Towards Leveraging Contrastively Pretrained Neural Audio Embeddings for Recommender Tasks. MuRS@RecSys 2024 - [i17]Philip Jordan, Florian Grötschla, Flint Xiaofeng Fan, Roger Wattenhofer:
Decentralized Federated Policy Gradient with Byzantine Fault-Tolerance and Provably Fast Convergence. CoRR abs/2401.03489 (2024) - [i16]Florian Grötschla, Joël Mathys, Robert Veres, Roger Wattenhofer:
CoRe-GD: A Hierarchical Framework for Scalable Graph Visualization with GNNs. CoRR abs/2402.06706 (2024) - [i15]Carlos Vonessen, Florian Grötschla, Roger Wattenhofer:
Next Level Message-Passing with Hierarchical Support Graphs. CoRR abs/2406.15852 (2024) - [i14]Rainer Feichtinger, Florian Grötschla, Lioba Heimbach, Roger Wattenhofer:
Benchmarking GNNs Using Lightning Network Data. CoRR abs/2407.07916 (2024) - [i13]Florian Grötschla, Luca A. Lanzendörfer, Marco Calzavara, Roger Wattenhofer:
AEye: A Visualization Tool for Image Datasets. CoRR abs/2408.04072 (2024) - [i12]Florian Grötschla, Joël Mathys, Christoffer Raun, Roger Wattenhofer:
GraphFSA: A Finite State Automaton Framework for Algorithmic Learning on Graphs. CoRR abs/2408.11042 (2024) - [i11]Florian Grötschla, Luca Strässle, Luca A. Lanzendörfer, Roger Wattenhofer:
Towards Leveraging Contrastively Pretrained Neural Audio Embeddings for Recommender Tasks. CoRR abs/2409.09026 (2024) - [i10]Florian Grötschla, Lioba Heimbach, Severin Richner, Roger Wattenhofer:
On the Lifecycle of a Lightning Network Payment Channel. CoRR abs/2409.15930 (2024) - [i9]Hubert Siuzdak, Florian Grötschla, Luca A. Lanzendörfer:
SNAC: Multi-Scale Neural Audio Codec. CoRR abs/2410.14411 (2024) - 2023
- [c3]Stefan Künzli, Florian Grötschla, Joël Mathys, Roger Wattenhofer:
SURF: A Generalization Benchmark for GNNs Predicting Fluid Dynamics. LoG 2023: 13 - [c2]Luca A. Lanzendörfer, Florian Grötschla, Emil Funke, Roger Wattenhofer:
DISCO-10M: A Large-Scale Music Dataset. NeurIPS 2023 - [i8]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:
Traffic4cast at NeurIPS 2022 - Predict Dynamics along Graph Edges from Sparse Node Data: Whole City Traffic and ETA from Stationary Vehicle Detectors. CoRR abs/2303.07758 (2023) - [i7]Luca A. Lanzendörfer, Florian Grötschla, Emil Funke, Roger Wattenhofer:
DISCO-10M: A Large-Scale Music Dataset. CoRR abs/2306.13512 (2023) - [i6]Eren Akbiyik, Florian Grötschla, Beni Egressy, Roger Wattenhofer:
Graphtester: Exploring Theoretical Boundaries of GNNs on Graph Datasets. CoRR abs/2306.17482 (2023) - [i5]Julian Minder, Florian Grötschla, Joël Mathys, Roger Wattenhofer:
SALSA-CLRS: A Sparse and Scalable Benchmark for Algorithmic Reasoning. CoRR abs/2309.12253 (2023) - [i4]Joël Mathys, Florian Grötschla, Kalyan Varma Nadimpalli, Roger Wattenhofer:
Flood and Echo: Algorithmic Alignment of GNNs with Distributed Computing. CoRR abs/2310.06970 (2023) - [i3]Stefan Künzli, Florian Grötschla, Joël Mathys, Roger Wattenhofer:
SURF: A Generalization Benchmark for GNNs Predicting Fluid Dynamics. CoRR abs/2310.20049 (2023) - 2022
- [i2]Florian Grötschla, Joël Mathys:
Hierarchical Graph Structures for Congestion and ETA Prediction. CoRR abs/2211.11762 (2022) - [i1]Florian Grötschla, Joël Mathys, Roger Wattenhofer:
Learning Graph Algorithms With Recurrent Graph Neural Networks. CoRR abs/2212.04934 (2022) - 2021
- [c1]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:
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) 2021: 251-278
Coauthor Index
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last updated on 2024-11-28 21:28 CET by the dblp team
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