Record link: 
http://hdl.handle.net/20.500.12708/193036
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Title: 
Expressivity-Preserving GNN Simulation
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Citation: 
Jogl, F., Thiessen, M., & Gärtner, T. (2023). Expressivity-Preserving GNN Simulation. In Advances in Neural Information Processing Systems. 37th Annual Conference on Neural Information Processing Systems (NeurIPS 2023), New Orleans, United States of America (the).
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Publication Type: 
Inproceedings - Full-Paper Contribution
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Language: 
English
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Authors: 
Jogl, Fabian 
Thiessen, Maximilian 
Gärtner, Thomas 
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Organisational Unit: 
E194-06 - Forschungsbereich Machine Learning 
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Published in: 
Advances in Neural Information Processing Systems 
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Date (published): 
21-Sep-2023
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Event name: 
37th Annual Conference on Neural Information Processing Systems (NeurIPS 2023) 
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Event date: 
10-Dec-2023 - 16-Dec-2023
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Event place: 
New Orleans, United States of America (the)
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Peer reviewed: 
Yes
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Keywords: 
Machine Learning; Neural Networks; Graphs; Graph Neural Networks; GNNs; expressivity
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Research Areas: 
Computer Science Foundations: 100%
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Science Branch: 
1020 - Informatik: 100%
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Appears in Collections:
Conference Paper

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