Results 31 to 40 of about 127,298 (253)
BMC Bioinformatics, 2021 Background This paper exploits recent developments in topological data analysis to present a pipeline for clustering based on Mapper, an algorithm that reduces complex data into a one-dimensional graph.
Ewan Carr +4 more
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Big Data and Cognitive Computing, 2022 Topological data analysis has recently found applications in various areas of science, such as computer vision and understanding of protein folding. However, applications of topological data analysis to natural language processing remain under-researched.
Ran Deng, Fedor Duzhin
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Event history and topological data analysis [PDF]
Biometrika, 2020 Summary Persistent homology is used to track the appearance and disappearance of features as we move through a nested sequence of topological spaces. Equating the nested sequence to a filtration and the appearance and disappearance of features to events, we show that simple event history methods can be used for the analysis of ...
Garside K +4 more
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Topological data analysis [PDF]
Nature Photonics, 2018 Topological data analysis (TDA) can broadly be described as a collection of data analysis methods that find structure in data. These methods include clustering, manifold estimation, nonlinear dimension reduction, mode estimation, ridge estimation and persistent homology. This paper reviews some of these methods.
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When remote sensing meets topological data analysis
Journal of Spectral Imaging, 2018 Hyperspectral remote sensing plays an increasingly important role in many scientific domains and everyday life problems. Indeed, this imaging concept ends up in applications as varied as catching tax-evaders red-handed by locating new construction and ...
Ludovic Duponchel
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Topological data analysis of zebrafish patterns [PDF]
Proceedings of the National Academy of Sciences, 2020 Self-organized pattern behavior is ubiquitous throughout nature, from fish schooling to collective cell dynamics during organism development. Qualitatively these patterns display impressive consistency, yet variability inevitably exists within pattern-forming systems on both microscopic and macroscopic scales.
Melissa R. McGuirl +2 more
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From Brain Lobes to Neurons: Navigating the Brain Using Advanced 3D Modeling and Visualization Tools
Journal of ImagingNeuroscience education must convey 3D structure with clarity and accuracy. Traditional 2D renderings are limited as they lose depth information and hinder spatial understanding.
Mohamed Rowaizak +2 more
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Topological data analysis for the string landscape
Journal of High Energy Physics, 2019 Persistent homology computes the multiscale topology of a data set by using a sequence of discrete complexes. In this paper, we propose that persistent homology may be a useful tool for studying the structure of the landscape of string vacua. As a scaled-
Alex Cole, Gary Shiu
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Challenges in Topological Object Data Analysis [PDF]
Sankhya A, 2018 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Patrangenaru, Vic +3 more
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Empowering Advanced Parametric Modes Clustering from Topological Data Analysis
Applied Sciences, 2021 Modal analysis is widely used for addressing NVH—Noise, Vibration, and Hardness—in automotive engineering. The so-called principal modes constitute an orthogonal basis, obtained from the eigenvectors related to the dynamical problem.
Tarek Frahi +4 more
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