14 citations · 43 across the 5 of their papers we have counts for
5 papers
Multi-Facet Clustering Variational Autoencoders
Fabian Falck, Haoting Zhang, Matthew Willetts +3
Work in deep clustering focuses on finding a single partition of data. However, high-dimensional data, such as images, typically feature multiple interesting characteristics one co…
TensOrMachine: Probabilistic Boolean Tensor Decomposition
Tammo Rukat, Chris C. Holmes, Christopher Yau
Boolean tensor decomposition approximates data of multi-way binary relationships as product of interpretable low-rank binary factors, following the rules of Boolean algebra. Here,…
Bayesian Boolean Matrix Factorisation
Tammo Rukat, Chris C. Holmes, Michalis K. Titsias +1
Boolean matrix factorisation aims to decompose a binary data matrix into an approximate Boolean product of two low rank, binary matrices: one containing meaningful patterns, the ot…
Statistical Inference in Hidden Markov Models using -segment Constraints
Michalis K. Titsias, Christopher Yau, Christopher C. Holmes
Hidden Markov models (HMMs) are one of the most widely used statistical methods for analyzing sequence data. However, the reporting of output from HMMs has largely been restricted…
A decision-theoretic approach for segmental classification
Christopher Yau, Christopher C. Holmes
This paper is concerned with statistical methods for the segmental classification of linear sequence data where the task is to segment and classify the data according to an underly…