Zobrazeno 1 - 10
of 1 425
pro vyhledávání: '"Schaub, Michael"'
Autor:
Telyatnikov, Lev, Bernardez, Guillermo, Montagna, Marco, Vasylenko, Pavlo, Zamzmi, Ghada, Hajij, Mustafa, Schaub, Michael T, Miolane, Nina, Scardapane, Simone, Papamarkou, Theodore
This work introduces TopoBenchmarkX, a modular open-source library designed to standardize benchmarking and accelerate research in Topological Deep Learning (TDL). TopoBenchmarkX maps the TDL pipeline into a sequence of independent and modular compon
Externí odkaz:
http://arxiv.org/abs/2406.06642
Residual connections and normalization layers have become standard design choices for graph neural networks (GNNs), and were proposed as solutions to the mitigate the oversmoothing problem in GNNs. However, how exactly these methods help alleviate th
Externí odkaz:
http://arxiv.org/abs/2406.02997
Autor:
Grande, Vincent P., Schaub, Michael T.
Topological Data Analysis (TDA) allows us to extract powerful topological and higher-order information on the global shape of a data set or point cloud. Tools like Persistent Homology or the Euler Transform give a single complex description of the gl
Externí odkaz:
http://arxiv.org/abs/2406.02300
Graph neural networks (GNNs) have emerged as powerful tools for processing relational data in applications. However, GNNs suffer from the problem of oversmoothing, the property that the features of all nodes exponentially converge to the same vector
Externí odkaz:
http://arxiv.org/abs/2406.02269
Autor:
Hoppe, Josef, Schaub, Michael T.
We define a model for random (abstract) cell complexes (CCs), similiar to the well-known Erd\H{o}s-R\'enyi model for graphs and its extensions for simplicial complexes. To build a random cell complex, we first draw from an Erd\H{o}s-R\'enyi graph, an
Externí odkaz:
http://arxiv.org/abs/2406.01999
Autor:
Frantzen, Florian, Schaub, Michael T.
Triggered by limitations of graph-based deep learning methods in terms of computational expressivity and model flexibility, recent years have seen a surge of interest in computational models that operate on higher-order topological domains such as hy
Externí odkaz:
http://arxiv.org/abs/2404.03434
Due to their flexibility to represent almost any kind of relational data, graph-based models have enjoyed a tremendous success over the past decades. While graphs are inherently only combinatorial objects, however, many prominent analysis tools are b
Externí odkaz:
http://arxiv.org/abs/2403.15023
Autor:
Baumgartner, Christian, Schaub, Michael Patrick, Wenger, Andreas, Malischnig, Doris, Augsburger, Mareike, Walter, Marc, Berger, Thomas, Stark, Lars, Ebert, David Daniel, Keough, Matthew T, Haug, Severin
Publikováno v:
Journal of Medical Internet Research, Vol 23, Iss 4, p e27463 (2021)
BackgroundDespite increasing demand for treatment among cannabis users in many countries, most users are not in treatment. Internet-based self-help offers an alternative for those hesitant to seek face-to-face therapy, though low effectiveness and ad
Externí odkaz:
https://doaj.org/article/5d179130a67343e7a7ff429a6d9569c6
Autor:
Weisel, Kiona K, Zarski, Anna-Carlotta, Berger, Thomas, Krieger, Tobias, Moser, Christian T, Schaub, Michael P, Görlich, Dennis, Berking, Matthias, Ebert, David D
Publikováno v:
Journal of Medical Internet Research, Vol 22, Iss 9, p e16450 (2020)
BackgroundInternet interventions have been shown to be effective in treating anxiety disorders. Most interventions to date focus on single disorders and disregard potential comorbidities. ObjectiveThe aim of this mixed-methods study was to investiga
Externí odkaz:
https://doaj.org/article/a86912cf5745412193e947e1acf88787
Autor:
Schaub, Michael Patrick, Berman, Anne H, López Pelayo, Hugo, Boumparis, Nikolaos, Khadjesari, Zarnie, Blankers, Matthijs, Gual, Antoni, Riper, Heleen, Pas, Lodewijk
Publikováno v:
Journal of Medical Internet Research, Vol 22, Iss 8, p e20368 (2020)
There is great potential for scaling up the delivery of brief interventions for alcohol and illicit drug use, given the increasing coverage of mobile devices and technologies for digital interventions, including apps for smartphones and tablets. Howe
Externí odkaz:
https://doaj.org/article/6bd274c9f7c34d2fb64846b347c3cacb