Moja prezentacja o topologicznej analizie danych (chociaż jest bardziej o topologii niż o danych)
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Updated
Jan 20, 2020 - TeX
Moja prezentacja o topologicznej analizie danych (chociaż jest bardziej o topologii niż o danych)
Persistent Homology as Stopping-Criterion for Voronoi Interpolation.
Topological Data Analysis on a Brain Network
Lecture notes for Topological Data Analysis.
Final project for MATH-478 of Spring 2021
LaTeX source code of the paper and poster of the paper Simplicial Neural Networks
Geometric Dynamic Variational Autoencoders (GD-VAEs) for learning embedding maps for nonlinear dynamics into general latent spaces. This includes methods for standard latent spaces or manifold latent spaces with specified geometry and topology. The manifold latent spaces can be based on analytic expressions or general point cloud representations.
DONUT: Database of Original and Non-Theoretical Applications of Topology
Code for the website of the NeurIPS 2020 workshop on 'Topological Data Analysis and Beyond'
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