Computing on Topological Domains

TopoBench is a Python library designed to standardize benchmarking and accelerate research in Topological Deep Learning

Geometries for 3D rendering, including normals, UVs and cell indices (faces). Perfect if you want to supercharge your dependency folder... with 30KB of geometries.

Representation Learning on Topological Domains

A general form for complex data

A simplicial complex and hypergraph visualization tool similar to Graphviz.

ggplot2 extension to visualize persistent homology

Tool to numerically solve and analyse simplicial Kuramoto models.

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.

R package for simplifying general computation on simplicial complexes

Finite Element Exterior Calculus on Coordinate-Free Simplicial Manifolds in Rust

R package porting Ripser-based persistent homology calculation engines from C++ via Rcpp. Currently ports Ripser (Vietoris-Rips complex) and Cubical Ripser (cubical complex).

Forman Ricci Curvature for Simplicial Complex.

Python bindings to Simplex Tree data structure (w/ C++)

A toolkit for discrete calculus.

Multidimensional interpolation using simplicial complexes.

Inductive Higher Order Knowledge Hypergraph Completion

Probabilistic activity driven model of temporal simplicial networks and its application on higher-order dynamics

UDiPH is a package that creates a new metric space where the points are uniformly sampled with respect to a global metric. It is oriented for creating Vietoris-Rips filtrations that are independent of the metric of the initial space.

Use hodge decomposition for trajectory analysis