A persistence-augmented neural network framework encodes local gradient flow regions and their hierarchy via the Morse-Smale complex to retain multi-scale localized topological information, outperforming global TDA descriptors on histopathology classification and 3D porous material regression while,
A survey of topological machine learning methods.Frontiers in Artificial Intelligence, Volume 4 - 2021, 2021
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Faster algorithms compute the integral bottleneck distance between PHTs in Õ(n^5) time and the max version in Õ(n^3) time for R^2 and Õ(n^5) for R^3.
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Persistence-Augmented Neural Networks
A persistence-augmented neural network framework encodes local gradient flow regions and their hierarchy via the Morse-Smale complex to retain multi-scale localized topological information, outperforming global TDA descriptors on histopathology classification and 3D porous material regression while,
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Computing the Bottleneck Distance between Persistent Homology Transforms
Faster algorithms compute the integral bottleneck distance between PHTs in Õ(n^5) time and the max version in Õ(n^3) time for R^2 and Õ(n^5) for R^3.