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An Introduction to Topological Data Analysis: Fundamental and Practical Aspects for Data Scientists

Frontiers in Artificial Intelligence, 2021
With the recent explosion in the amount, the variety, and the dimensionality of available data, identifying, extracting, and exploiting their underlying structure has become a problem of fundamental importance for data analysis and statistical learning ...
Frédéric Chazal, Bertrand Michel
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Topological Data Analysis

, 2022
It has been observed since a long time that data are often carrying interesting topological and geometric structures. Characterizing such structures and providing efficient tools to infer and exploit them is a challenging problem that asks for new mathematics and that is motivated by a real need from applications.
Boissonnat, Jean-Daniel, Chazal, Frédéric, Michel, Bertrand   +2 more
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Topological Data Analysis Helps to Improve Accuracy of Deep Learning Models for Fake News Detection Trained on Very Small Training Sets

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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Topological data analysis in biomedicine: A review

Journal of Biomedical Informatics, 2022
Significant technological advances made in recent years have shepherded a dramatic increase in utilization of digital technologies for biomedicine- everything from the widespread use of electronic health records to improved medical imaging capabilities and the rising ubiquity of genomic sequencing contribute to a "digitization" of biomedical research ...
Yara Skaf, Reinhard C. Laubenbacher
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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, Alexandria Volkening, Björn Sandstede   +2 more
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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, Gjoka A, Henderson R, Johnson H, Makarenko I   +4 more
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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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From Brain Lobes to Neurons: Navigating the Brain Using Advanced 3D Modeling and Visualization Tools

Journal of Imaging
Neuroscience 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, Ahmad Farhat, Reem Khalil   +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, Bubenik, Peter, Paige, Robert L., Osborne, Daniel   +3 more
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