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We propose in this paper to compare null models and real datasets using Persistent homology. (PH). PH is part of topological data analysis (TDA), and offers a.
We propose in this paper to compare null models and real datasets using Persistent homology (PH). PH is part of topological data analysis (TDA), and offers a ...
Jul 28, 2023 · One of the most elusive challenges within the area of topological data analysis is understanding the distribution of persistence diagrams ...
COMPARISONS OF NULL MODELS WITH TOPOLOGICAL DATA ANALYSIS · 1: Standardizing Acquisition & Analysis in Preclinical fMRI · 2: SPATIO-TEMPORAL MODEL FOR DYNAMIC ...
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Jan 13, 2024 · This manuscript explores the capability of topological data analysis (TDA) based on homology theory (HT: a subfield of algebraic topology) to extract relevant ...
Null models are crucial in determining whether brain networks display certain features to a greater extent than expected by chance under a null hypothesis.
Topological Data Analysis (TDA) has been praised by researchers for its ability to capture intricate shapes and structures within data.
For both the spatial growth and the Erd˝ os-Rényi null models, we have reported the average of the topological similarity across the four surrogate null model ...
In addition, we observed relative differences between what we discovered in the null models, and the actual data increased drastically when the dimensions were ...
Aug 21, 2024 · Develops statistical tests for comparing topological features between datasets or against null models; Permutation tests assess significance ...