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Published in 2019 at "International Journal of Quantum Chemistry"
DOI: 10.1002/qua.26133
Abstract: Topological Data Analysis (TDA) is a powerful mathematical theory, largely unexplored in theoretical chemistry. In this work we demonstrate how TDA provides new insights into topological features of electron densities and reduced density gradients, by…
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Keywords:
chemistry;
analysis;
analysis perspective;
perspective noncovalent ... See more keywords
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Published in 2018 at "Analytica chimica acta"
DOI: 10.1016/j.aca.2017.11.029
Abstract: Analytical chemistry is rapidly changing. Indeed we acquire always more data in order to go ever further in the exploration of complex samples. Hyperspectral imaging has not escaped this trend. It quickly became a tool…
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Keywords:
imaging data;
data sets;
data analysis;
topological data ... See more keywords
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Published in 2021 at "NeuroImage"
DOI: 10.1016/j.neuroimage.2021.118245
Abstract: Developing sensitive and reliable methods to distinguish normal and abnormal brain states is a key neuroscientific challenge. Topological Data Analysis, despite its relative novelty, already generated many promising applications, including in neuroscience. We conjecture its…
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Keywords:
data analysis;
topological data;
analysis;
connectivity ... See more keywords
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Published in 2020 at "Physica D: Nonlinear Phenomena"
DOI: 10.1016/j.physd.2020.132446
Abstract: Abstract Traditionally, computation of Lyapunov exponents has been the marque method for identifying chaos in a time series. Recently, new methods have emerged for systems with both known and unknown models to produce a definitive…
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Keywords:
chaos detection;
time series;
topological data;
time ... See more keywords
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Published in 2022 at "Chaos"
DOI: 10.1063/5.0090114
Abstract: The investigation of dynamical processes on networks has been one focus for the study of contagion processes. It has been demonstrated that contagions can be used to obtain information about the embedding of nodes in…
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Keywords:
contagion maps;
contagion;
data analysis;
analysis truncated ... See more keywords
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Published in 2022 at "Advances in Physics: X"
DOI: 10.1080/23746149.2023.2202331
Abstract: Topological data analysis refers to approaches for systematically and reliably computing abstract ``shapes'' of complex data sets. There are various applications of topological data analysis in life and data sciences, with growing interest among physicists.…
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Keywords:
physics;
topological data;
data analysis;
machine learning ... See more keywords
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Published in 2018 at "Inverse Problems"
DOI: 10.1088/1361-6420/aae993
Abstract: This work combines a level-set approach and the optimal transport-based Wasserstein distance in a data assimilation framework. The primary motivation of this work is to reduce assimilation artifacts resulting from the position and observation error…
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Keywords:
using wasserstein;
topological data;
distance;
data assimilation ... See more keywords
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Published in 2020 at "IEEE Transactions on Visualization and Computer Graphics"
DOI: 10.1109/tvcg.2019.2934594
Abstract: With the rapid adoption of machine learning techniques for large-scale applications in science and engineering comes the convergence of two grand challenges in visualization. First, the utilization of black box models (e.g., deep neural networks)…
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Keywords:
scalable topological;
topology;
topological data;
data analysis ... See more keywords
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Published in 2018 at "European Respiratory Journal"
DOI: 10.1183/13993003.congress-2018.pa5435
Abstract: Background: Molecular stratification of childhood asthma could enable targeted therapy.Aims: Unbiased analysis of gene expression in paediatric severe (SA) and moderate/mild asthma (MA) blood sampl ...
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Keywords:
analysis;
topological data;
blood;
gene expression ... See more keywords
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Published in 2020 at "BMC Bioinformatics"
DOI: 10.1186/s12859-020-03659-3
Abstract: Background Machine learning models for repeated measurements are limited. Using topological data analysis (TDA), we present a classifier for repeated measurements which samples from the data space and builds a network graph based on the…
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Keywords:
classification;
data analysis;
topological data;
svm ... See more keywords
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Published in 2020 at "PLoS computational biology"
DOI: 10.1371/journal.pcbi.1008407
Abstract: By modifying and calibrating an active vertex model to experiments, we have simulated numerically a confluent cellular monolayer spreading on an empty space and the collision of two monolayers of different cells in an antagonistic…
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Keywords:
data analysis;
topological data;
antagonistic migration;
numerical simulations ... See more keywords