<div class="csl-bib-body">
<div class="csl-entry">Jin, E., Bronstein, M. M., Ceylan, I. I., & Lanzinger, M. (2024). Homomorphism Counts for Graph Neural Networks: All About That Basis. In <i>Forty-first International Conference on Machine Learning</i>. Forty-first International Conference on Machine Learning, Austria. http://hdl.handle.net/20.500.12708/210485</div>
</div>
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/210485
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dc.description.sponsorship
WWTF Wiener Wissenschafts-, Forschu und Technologiefonds
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dc.language.iso
en
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dc.subject
Graph Learning
en
dc.subject
Homomorphism Counting
en
dc.subject
Deep Learning
en
dc.subject
Graph Neural Networks
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dc.subject
Geometric Deep Learning
en
dc.title
Homomorphism Counts for Graph Neural Networks: All About That Basis
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dc.type
Inproceedings
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dc.type
Konferenzbeitrag
de
dc.contributor.affiliation
University of Oxford, United Kingdom of Great Britain and Northern Ireland (the)
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dc.contributor.affiliation
University of Oxford, United Kingdom of Great Britain and Northern Ireland (the)
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ICT22-011
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Full-Paper Contribution
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tuw.booktitle
Forty-first International Conference on Machine Learning
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true
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Decompose and Conquer: Fast Query Processing via Decomposition
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Logic and Computation
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Information Systems Engineering
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tuw.linking
https://arxiv.org/pdf/2402.08595v5
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E192-02 - Forschungsbereich Databases and Artificial Intelligence
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Forty-first International Conference on Machine Learning
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21-07-2024
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27-07-2024
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On Site
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AT
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Jin, Emily
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Informatik
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100
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WWTF Wiener Wissenschafts-, Forschu und Technologiefonds
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University of Oxford
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University of Oxford
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E192-02 - Forschungsbereich Databases and Artificial Intelligence
