ilanfri

Quick List of Resources for Topological Data Analysis with Emphasis on Machine Learning

This is just a quick list of resourses on TDA that I put together for @rickasaurus after he was asking for links to papers, books, etc on Twitter and is by no means an exhaustive list.

Survey Papers

Both Carlsson's and Ghrist's survey papers offer a very good introduction to the subject

Topology and Data by Gunnar Carlsson
Barcodes: The Persistent Topology of Data by Robert Ghrist

Other Papers and Web Resources

Extracting insights from the shape of complex data using topology A good introductory paper in Nature on the Mapper algorithm.

	data {
	int<lower=0> num_obs; // number of observations
	real y[num_obs]; // Observed value
	int time[num_obs]; // time

	}
	parameters {
	//weakly uninformative priors, K on log base 10 scale
	vector[100] log_K;
	real<lower=0,upper=100> p0;

	#------------------------------------------------------------------------------
	rm(list = ls())

	set.seed(50)

	# function for generating random draws from multivariate distribution
	# n = number of draws; p = number of variables
	# u = mean of each variable; s = SD of each variable
	# corMat = correlation matrix
	mvrnorm <- function(n, p, u, s, corMat) {