Computing on Topological Domains
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Updated
Oct 31, 2025 - Jupyter Notebook
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.
Use hodge decomposition for trajectory analysis
Model and represent Simplicial Complexes and their Cochains. Provides a clean interface to calculate Betti numbers and (discrete) 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.
A toolkit for discrete calculus.
Python bindings to Simplex Tree data structure (w/ C++)
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
AHORN is a comprehensive repository of research-quality simplicial complex, cell complex, and hypergraph datasets for higher-order network science.
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