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Found 3 papers, 2 papers with code
$G$-Mapper: Learning a Cover in the Mapper Construction
The Mapper algorithm is a visualization technique in topological data analysis (TDA) that outputs a graph reflecting the structure of a given dataset.
Sketching Merge Trees for Scientific Data Visualization
That is, given a large set T of merge trees, we would like to find a much smaller basis set S such that each tree in T can be approximately reconstructed from a linear combination of merge trees in S. A set of high-dimensional vectors can be sketched via matrix sketching techniques such as principal component analysis and column subset selection.
TopoAct: Visually Exploring the Shape of Activations in Deep Learning
To understand how such performance is achieved, we probe a trained deep neural network by studying neuron activations, i. e., combinations of neuron firings, at various layers of the network in response to a particular input.
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