Computing on Topological Domains
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Updated
Dec 20, 2024 - Jupyter Notebook
Computing on Topological Domains
TopoBenchmark 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
Forman Ricci Curvature for Simplicial Complex.
R package porting Ripser-based persistent homology calculation engines from C++ via Rcpp. Currently ports Ripser (Vietoris-Rips complex) and Cubical Ripser (cubical complex).
Python bindings to Simplex Tree data structure (w/ C++)
Multidimensional interpolation using simplicial complexes.
Finite Element Exterior Calculus on Coordinate-Free Simplicial Manifolds in Rust
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.
A toolkit for discrete calculus.
Use hodge decomposition for trajectory analysis
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