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pro vyhledávání: '"Klepper, Solveig"'
Autor:
Klepper, Solveig
Diffusion models have emerged from various theoretical and methodological perspectives, each offering unique insights into their underlying principles. In this work, we provide an overview of the most prominent approaches, drawing attention to their
Externí odkaz:
http://arxiv.org/abs/2409.00374
Autor:
Klepper, Solveig, von Luxburg, Ulrike
Graph auto-encoders are widely used to construct graph representations in Euclidean vector spaces. However, it has already been pointed out empirically that linear models on many tasks can outperform graph auto-encoders. In our work, we prove that th
Externí odkaz:
http://arxiv.org/abs/2211.01858
Autor:
Klepper, Solveig, Elbracht, Christian, Fioravanti, Diego, Kneip, Jakob, Rendsburg, Luca, Teegen, Maximilian, von Luxburg, Ulrike
Originally, tangles were invented as an abstract tool in mathematical graph theory to prove the famous graph minor theorem. In this paper, we showcase the practical potential of tangles in machine learning applications. Given a collection of cuts of
Externí odkaz:
http://arxiv.org/abs/2006.14444
Akademický článek
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Autor:
Burger KE; University of Tübingen., Klepper S; University of Tübingen, Tübingen AI Center., von Luxburg U; University of Tübingen, Tübingen AI Center., Baumdicker F; Institute for Bioinformatics and Medical Informatics, University of Tübingen franz.baumdicker@uni-tuebingen.de.
Publikováno v:
Genome research [Genome Res] 2024 Oct 21. Date of Electronic Publication: 2024 Oct 21.
