Zobrazeno 1 - 10
of 362
pro vyhledávání: '"Topological machine learning"'
Large density fluctuations of conserved charges have been proposed as a promising signature for exploring the QCD critical point in heavy-ion collisions. These fluctuations are expected to exhibit a fractal or scale-invariant behavior, which can be p
Externí odkaz:
http://arxiv.org/abs/2412.06151
Topological signals are variables or features associated with both nodes and edges of a network. Recently, in the context of Topological Machine Learning, great attention has been devoted to signal processing of such topological signals. Most of the
Externí odkaz:
http://arxiv.org/abs/2412.05132
Akademický článek
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Novel Topological Machine Learning Methodology for Stream-of-Quality Modeling in Smart Manufacturing
This paper presents a topological analytics approach within the 5-level Cyber-Physical Systems (CPS) architecture for the Stream-of-Quality assessment in smart manufacturing. The proposed methodology not only enables real-time quality monitoring and
Externí odkaz:
http://arxiv.org/abs/2404.14728
Publikováno v:
Mathematics 2022, 10(17), 3086
In this work, we develop a pipeline that associates Persistence Diagrams to digital data via the most appropriate filtration for the type of data considered. Using a grid search approach, this pipeline determines optimal representation methods and pa
Externí odkaz:
http://arxiv.org/abs/2309.15276
Autor:
Conti, Francesco, Banchelli, Martina, Bessi, Valentina, Cecchi, Cristina, Chiti, Fabrizio, Colantonio, Sara, D'Andrea, Cristiano, de Angelis, Marella, Moroni, Davide, Nacmias, Benedetta, Pascali, Maria Antonietta, Sorbi, Sandro, Matteini, Paolo
The cerebrospinal fluid (CSF) of 19 subjects who received a clinical diagnosis of Alzheimer's disease (AD) as well as of 5 pathological controls have been collected and analysed by Raman spectroscopy (RS). We investigated whether the raw and preproce
Externí odkaz:
http://arxiv.org/abs/2309.03664
One of the main challenges of Topological Data Analysis (TDA) is to extract features from persistent diagrams directly usable by machine learning algorithms. Indeed, persistence diagrams are intrinsically (multi-)sets of points in $\mathbb{R}^2$ and
Externí odkaz:
http://arxiv.org/abs/2112.15210
Publikováno v:
In Neuroscience 15 January 2023 509:43-50
Autor:
Wu, Chengyuan, Hargreaves, Carol Anne
Topological data analysis is a relatively new branch of machine learning that excels in studying high dimensional data, and is theoretically known to be robust against noise. Meanwhile, data objects with mixed numeric and categorical attributes are u
Externí odkaz:
http://arxiv.org/abs/2003.04584
Akademický článek
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