Principled methods for mixtures processing - Inria - Institut national de recherche en sciences et technologies du numérique
Hdr Année : 2022

Principled methods for mixtures processing

Antoine Liutkus

Résumé

This document is my thesis for getting the habilitation à diriger des recherches, which is the french diploma that is required to fully supervise Ph.D. students. It summarizes the research I did in the last 15 years and also provides the short­term research directions and applications I want to investigate. Regarding my past research, I first describe the work I did on probabilistic audio modeling, including the separation of Gaussian and α­stable stochastic processes. Then, I mention my work on deep learning applied to audio, which rapidly turned into a large effort for community service. Finally, I present my contributions in machine learning, with some works on hardware compressed sensing and probabilistic generative models. My research programme involves a theoretical part that revolves around probabilistic machine learning, and an applied part that concerns the processing of time series arising in both audio and life sciences.
Fichier principal
Vignette du fichier
HDR.pdf (18.5 Mo) Télécharger le fichier
Origine Fichiers produits par l'(les) auteur(s)

Dates et versions

tel-03578077 , version 1 (17-02-2022)

Identifiants

  • HAL Id : tel-03578077 , version 1

Citer

Antoine Liutkus. Principled methods for mixtures processing. Signal and Image Processing. Université de Montpellier, 2022. ⟨tel-03578077⟩
144 Consultations
213 Téléchargements

Partager

More