A high-performance topological machine learning toolbox in Python

Ripser: efficient computation of Vietoris–Rips persistence barcodes

A standalone version of Urban Pulse

High performance implementation of Vietoris-Rips persistence.

Python code to directly compute persistence images (PIs) from data (time-series or images) using deep learning.

Julia library providing functionality for modeling Simplicial Complexes and Cochains over them. Its main feature is a clean interface to calculate Betti numbers and Hodge decompositions.

Computing Betti numbers from simplicial complexes.

Matlab and Python code to compute perturbed topological signatures (PTS), an efficient topological representation that lies on the Grassmann manifold.

Recon - A fast algorithm to compute Reeb graphs

Topological Data Analysis using Contour Trees

Python bindings and API for the flagser C++ library (https://github.com/luetge/flagser).

Computation of persistence Steenrod barcodes

Simple Ripser wrapper in Julia

Python implementation of polygon-inclusion algorithm based on the winding number

Maurer-Cartan-Lie frame connections ∇ Grassmann.jl TensorField derivations

A Testing Framework for Decision-Optimization Model Learning Algorithms

This project uses topological methods to track evasion paths in mobile sensor networks.

Computes a Witness Complex for a given set of landmarks and witnesses.

A fork to optimize interval matching in the bootstrap case; also extends to data with arbitrary (precomputed) distance metrics.