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pro vyhledávání: '"Juliá E"'
Autor:
Bergner, Julia E.
Publikováno v:
Matematica 1 (2022), no. 4, 886-912
The notion of a simplicial set originated in algebraic topology, and has also been utilized extensively in category theory, but until relatively recently was not used outside of those fields. However, with the increasing prominence of higher categori
Externí odkaz:
http://arxiv.org/abs/2411.18561
Autor:
Bergner, Julia E.
Publikováno v:
in Equivariant Topology and Derived Algebra (S. Balchin et al, editors), London Mathematical Society Lecture Note Series 474 (2021)
The definition of the homotopy limit of a diagram of left Quillen functors of model categories has been useful in a number of applications. In this paper we review its definition and summarize some of these applications. We conclude with a discussion
Externí odkaz:
http://arxiv.org/abs/2411.18546
Autor:
Bergner, Julia E.
We give an introduction to the theory of 2-Segal sets, and two of the main applications of them: Hall algebras and a discrete version of Waldhausen's $S_\bullet$-construction. We present several combinatorial examples and how these constructions can
Externí odkaz:
http://arxiv.org/abs/2411.18544
Autor:
Agostini, Andrea, Chopard, Daphné, Meng, Yang, Fortin, Norbert, Shahbaba, Babak, Mandt, Stephan, Sutter, Thomas M., Vogt, Julia E.
Multimodal data integration and label scarcity pose significant challenges for machine learning in medical settings. To address these issues, we conduct an in-depth evaluation of the newly proposed Multimodal Variational Mixture-of-Experts (MMVM) VAE
Externí odkaz:
http://arxiv.org/abs/2411.10356
Autor:
Chopard, Daphné, Laguna, Sonia, Chin-Cheong, Kieran, Dietz, Annika, Badura, Anna, Wellmann, Sven, Vogt, Julia E.
General movements (GMs) are spontaneous, coordinated body movements in infants that offer valuable insights into the developing nervous system. Assessed through the Prechtl GM Assessment (GMA), GMs are reliable predictors for neurodevelopmental disor
Externí odkaz:
http://arxiv.org/abs/2411.09821
The spatio-temporal nature of live-cell microscopy data poses challenges in the analysis of cell states which is fundamental in bioimaging. Deep-learning based segmentation or tracking methods rely on large amount of high quality annotations to work
Externí odkaz:
http://arxiv.org/abs/2411.03924
Autor:
Reizinger, Patrik, Bizeul, Alice, Juhos, Attila, Vogt, Julia E., Balestriero, Randall, Brendel, Wieland, Klindt, David
Supervised learning has become a cornerstone of modern machine learning, yet a comprehensive theory explaining its effectiveness remains elusive. Empirical phenomena, such as neural analogy-making and the linear representation hypothesis, suggest tha
Externí odkaz:
http://arxiv.org/abs/2410.21869
Concept-based machine learning methods have increasingly gained importance due to the growing interest in making neural networks interpretable. However, concept annotations are generally challenging to obtain, making it crucial to leverage all their
Externí odkaz:
http://arxiv.org/abs/2410.18705
Finding clusters of data points with similar characteristics and generating new cluster-specific samples can significantly enhance our understanding of complex data distributions. While clustering has been widely explored using Variational Autoencode
Externí odkaz:
http://arxiv.org/abs/2410.16910
The structure of many real-world datasets is intrinsically hierarchical, making the modeling of such hierarchies a critical objective in both unsupervised and supervised machine learning. Recently, novel approaches for hierarchical clustering with de
Externí odkaz:
http://arxiv.org/abs/2410.07858