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.

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

Computing Betti numbers from simplicial complexes.

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

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.

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