A curated list of topological data analysis (TDA) resources and links.
A curated list of Topological Data Analysis (TDA) tools and resources.
If you know of any other tools or resources, read Contribution Guidelines and feel free to fork/PR or open a new issue.
A Short Course in Computational Geometry and Topology - Edelsbrunner, Herbert.
Computational Homology (Applied Mathematical Sciences) - Kaczynski, Mischaikow, Mrozek.
:open_book: Computational Topology: An Introduction - Herbert Edelsbrunner, John L Harer.
:open_book: Computational Topology for Data Analysis - Tamal Krishna Dey, Yusu Wang.
:open_book: Elementary Applied Topology - Robert Ghrist.
Fundamentals of Brain Network Analysis - Fundamentals of Brain Network Analysis.
Geometric and Topological Inference - Boissonnat, Chazal, Yvinec.
:open_book: Persistence Theory: From Quiver Representations to Data Analysis - Steve Y Oudot.
Topological and Statistical Methods for Complex Data: Tackling Large-Scale, High-Dimensional, and Multivariate Data Spaces - Bennett, Janine, Vivodtzev, Fabien, Pascucci, Valerio.
Topological Based Machine Learning Methods - Alex Georges.
Topological Data Analysis for Genomics and Evolution: Topology in Biology - Raul Rabadan, Andrew J Blumberg.
Topological Data Analysis for Scientific Visualization - Tierny, Julien.
:open_book: Topological Methods for 3D Point Cloud Processing - William Joseph Beksi.
:open_book: Topology for Computing - AFRA J ZOMORODIAN.
Topological Methods in Data Analysis and Visualization: Theory, Algorithms, and Applications
Topological Methods in Data Analysis and Visualization: Theory, Algorithms, and Applications II
Topological Methods in Data Analysis and Visualization: Theory, Algorithms, and Applications III
Topological Methods in Data Analysis and Visualization: Theory, Algorithms, and Applications IV
Topology-based Methods in Visualization - Hauser, Helwig, Hagen, Hans, Theisel, Holger (Eds.)
A Fuzzy Clustering Algorithm for the Mode Seeking Framework - Bonis, Oudot.
A topological data analysis based classification method for multiple measurements - Riihimäki, Chachólski, Theorell, Hillert, Ramanujam.
A User's Guide to Topological Data Analysis - Elizabeth Munch.
An introduction to Topological Data Analysis: fundamental and practical aspects for data scientists - Chazal, Michel.
Barcodes: The Persistent Topology of Data - Robert Ghrist.
Computing Persistent Homology (Discrete and Computational Geometry) - Zomorodian, Carlsson.
Deep Learning with Topological Signatures - Hofer, Kwitt, Niethammer, Uhl.
Designing machine learning workflows with an application to topological data analysis - Cawi, La Rosa, Nehorai.
Introduction to the R package TDA - Fasy, Jisu Kim, Lecci, Clément Maria, Millman, Rouvreau.
Homological Algebra and Data - Robert Ghrist.
Large Scale computation of Means and Clusters for Persistence Diagrams using Optimal Transport - Lacombe, Cuturi, OUDOT.
Sampling real algebraic varieties for topological data analysis - Dufresne, Edwards, Harrington, Hauenstein.
Stratifying Multiparmeter Persistent Homology - Harriington, Otter, Schenck, Tillmann.
Text Mining using Topological Data Analysis. An introduction - Carrazana, Chong.
Topology and Data - Gunnar Carlsson.
Topological Data Analysis - Larry Wasserman.
Topological Data Analysis and Its Application to Time-Series Data Analysis - Umeda, Kaneko, Kikuchi.
Topological Data Analysis and Machine Learning Theory - Carlsson , Jardine, Feichtner-Kozlov, Morozov.
Topological Data Analysis for Object Data - Patrangenaru, Bubenik, Paige, Osborne .
Two-Tier Mapper: a user-independent clustering method for global gene expression analysis based on topology - Jeitziner, Carrière, Rougemont, Oudot, Hess, Brisken.
Why Topology for Machine Learning and Knowledge Extraction? - Massimo Ferri.
Computational Topology and Data Analysis - Course is not active, but the course notes are useful.
Topological Data Analysis - Course is not active, but the course notes are useful.
Topics in topology: Scientific and engineering applications of algebraic topology - 2013 lecture series.
Ctl - (C++11 library) A set of generic tools for Building Neighborhood Graphs and Cellular Complexes, Computing (persistent) homology over finite fields, Parallel algorithms for homology. an be used with c++, Python, MATLAB and R.
Knotter - Implementation of Mapper algorithm for TDA.
RIVET - For the visualization and analysis of two-parameter persistent homology with Python API.
TdaToolbox - Some tools that may be applied to data science in general.
TTk - Topological data analysis in scientific visualization. Can be used with C++, python.
Dionysus - Computing persistent (co)homology, Implementation of the Persistent (co)homology computation, Vineyards, Zigzag persistent homology algorithms.
PHAT - Persistent Homology Algorithm Toolbox.
Topology ToolKit (TTK) - Efficient, generic and easy and Topological data analysis and visualization
GDA Public - Several fundamental tools by Geometric Data Analytics Inc. geomdata
Giotto TDA(GTDA) - A high-performance topological machine learning toolbox
GUDHI - Geometry Understanding in Higher Dimensional with a Python interface.
KeplerMapper - TDA Mapper algorithm for visualization of high-dimensional data. it can make use of Scikit-Learn API compatible cluster and scaling algorithms.
Kohonen - Kohonen-style vector quantizers: Self-Organizing Map (SOM), Neural Gas, and Growing Neural Gas.
Mapper Implementation - Topological Data Analysis for high dimensional dataset exploration.
MoguTDA - Numerical calculation of algebraic topology in an application to topological data analysis: implicial complex, and the estimation of homology and Betti numbers.
Persim - package for many tools used in analyzing Persistence Diagrams
Python Mapper - Mapper algorithm implementation + graphical user interface.
Qsv - Data structure visualizer.
Ripser - lean persistent homology package.
Scikit-TDA - For non-topologists.
Giotto-TDA - A scikit-learn
- compatible library for end-to-end topological machine learning including Mapper, persistent homology, vectorization methods for persistence diagrams, and preprocessing components for time series, graphs, images, and point clouds (paper).
ScTDA - It includes tools for the preprocessing, analysis, and exploration of single-cell RNA-seq data based on topological representations.
Topology ToolKit (TTK) - Efficient, generic and easy and Topological data analysis and visualization
TMAP - Population-scale microbiome data analysis.
TDA - Tools for the statistical analysis of persistent homology and for density clustering.
TDAmapper - An R package for using discrete Morse theory to analyze a data set using the Mapper algorithm described in G. Singh, F. Memoli, G. Carlsson (2007).
TDAstats - Computing persistent homology.
Spark Mapper - Estimating a lower dimensional simplicial complex from a dataset.
Spark TDA - Scalable topological data analysis package.
An algebraic topological method for multimodal brain networks comparisons
Complex Brain Network Analysis and Its Applications to Brain Disorders: A Survey
Applied Topological Data Analysis to Deep Learning? Hands-on Arrhythmia Classification!
From Topological Data Analysis to Deep Learning: No Pain No Gain
On Characterizing the Capacity of Neural Networks Using Algebraic Topology
Using Topological Data Analysis to Understand the Behavior of Convolutional Neural Networks
An Algebraic Geometry Perspective on Topological Data Analysis
Topological Data Analysis - UFL.
Topological Data Analysis - IBM.