Generative source separation methods such as non-negative matrix factorization (NMF) or
auto-encoders, rely on the assumption of an output probability density. Generative …

Providing prior knowledge about sources to guide source separation is known to be useful
in many audio applications. In this paper we present two tensor factorization models for …

We provide an overview of matrix and tensor factorization methods from a Bayesian
perspective, giving emphasis on both the inference methods and modeling techniques …

Generalised coupled tensor factorisation is a recently proposed algorithmic framework for
simultaneously estimating tensor factorisation models where several observed tensors can …

In this paper, we propose a low-rank tensor deconvolution problem which seeks multiway
replicative patterns and corresponding activating tensors of rank-1. An alternating least …

US9978379B2 - Multi-channel encoding and/or decoding using non-negative tensor
factorization - Google Patents US9978379B2 - Multi-channel encoding and/or decoding using …

This report focuses on so-called weighted variants of nonnnegative matrix factorization
(NMF) and more generally nonnnegative tensor factorization (NTF) approximations. First, we …

This thesis proposes a unified probabilistic framework for modelling multiway data. Our
approach establishes a novel link between probabilistic graphical models and tensor …

Traditionally, signal-processing and pattern-recognition algorithms tend to look at signals
under the assumption of little, if any, interference. The vast majority of algorithms for speech …

A novel blind deconvolution is proposed to seek for basis patterns and their location maps
inside a nonnegative data matrix. Basis patterns can have different sizes, and shift in …