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Found 5 papers, 2 papers with code
Convolutional Persistence Transforms
In this paper, we consider topological featurizations of data defined over simplicial complexes, like images and labeled graphs, obtained by convolving this data with various filters before computing persistence.
Improving Metric Dimensionality Reduction with Distributed Topology
We propose a novel approach to dimensionality reduction combining techniques of metric geometry and distributed persistent homology, in the form of a gradient-descent based method called DIPOLE.
From Geometry to Topology: Inverse Theorems for Distributed Persistence
Moreover, the quasi-isometry bounds depend on the size of the subsets taken, so that as the size of these subsets goes from small to large, the invariant interpolates between a purely geometric one and a topological one.
A Fast and Robust Method for Global Topological Functional Optimization
Topological statistics, in the form of persistence diagrams, are a class of shape descriptors that capture global structural information in data.
Geometric Fusion via Joint Delay Embeddings
We introduce geometric and topological methods to develop a new framework for fusing multi-sensor time series.
