43 citations · 96 across the 4 of their papers we have counts for
4 papers
Distributed Bayesian Matrix Factorization with Limited Communication
Xiangju Qin, Paul Blomstedt, Eemeli Leppäaho +2
Bayesian matrix factorization (BMF) is a powerful tool for producing low-rank representations of matrices and for predicting missing values and providing confidence intervals. Scal…
GFA: Exploratory Analysis of Multiple Data Sources with Group Factor Analysis
Eemeli Leppäaho, Muhammad Ammad-ud-din, Samuel Kaski
The R package GFA provides a full pipeline for factor analysis of multiple data sources that are represented as matrices with co-occurring samples. It allows learning dependencies…
Sparse group factor analysis for biclustering of multiple data sources
Kerstin Bunte, Eemeli Leppäaho, Inka Saarinen +1
Motivation: Modelling methods that find structure in data are necessary with the current large volumes of genomic data, and there have been various efforts to find subsets of genes…
Bayesian multi-tensor factorization
Suleiman A. Khan, Eemeli Leppäaho, Samuel Kaski
We introduce Bayesian multi-tensor factorization, a model that is the first Bayesian formulation for joint factorization of multiple matrices and tensors. The research problem gene…