104 citations · 171 across the 9 of their papers we have counts for
3 papers · 1 filter
A Variational Autoencoder for Probabilistic Non-Negative Matrix Factorisation
Steven Squires, Adam Prügel Bennett, Mahesan Niranjan
We introduce and demonstrate the variational autoencoder (VAE) for probabilistic non-negative matrix factorisation (PAE-NMF). We design a network which can perform non-negative mat…
A numerical measure of the instability of Mapper-type algorithms
Francisco Belchí, Jacek Brodzki, Matthew Burfitt +1
Mapper is an unsupervised machine learning algorithm generalising the notion of clustering to obtain a geometric description of a dataset. The procedure splits the data into possib…
Minimum description length as an objective function for non-negative matrix factorization
Steven Squires, Adam Prugel Bennett, Mahesan Niranjan
Non-negative matrix factorization (NMF) is a dimensionality reduction technique which tends to produce a sparse representation of data. Commonly, the error between the actual and r…