Remi GRIBONVAL
Articles de cet auteur
Apr 27
Code release: Physics-Driven Cosparse Analysis and Convex Blind Calibration
The PHYSALIS Matlab code allows to reproduce the experiments from a series of papers from our group on cosparse (=analysis flavor of sparse) source localization, for both acoustic inverse problems and EEG inverse problems. It is available here The CBC4CS code allows to reproduce convex blind calibration experiments in the context of compressive sensing. It …
Sep 08
Ne manquez pas la prochaine Journée Science et Musique, le 1er octobre au Diapason à Rennes
Tous les détails sur le site de la Journée Sciences et Musiqe, jsm.irisa.fr
Jul 08
(closed) PhD offer – Interactive Navigation for a Video Audio True Experience @ PANAMA, Inria Rennes
Details and appliication here
Jun 16
Paper + code on random sampling of bandlimited signals on graphs
Our paper on Random Sampling of Bandlimited Signals on Graphs has been accepted for publication in Applied and Computational Harmonic Analysis . Read it on arXiv:1511.05118 or hal:hal-01320214 Download the code at http://grsamplingbox.gforge.inria.fr/
May 25
2016 Award for Outstanding Contributions in Neural Systems
Congratulations to Antoine Deleforge (new PANAMA team member), Florence Forbes (MISTIS team) and Radu Horaud (PERCEPTION team) who received the 2016 Hojjat Adeli Award for Outstanding Contributions in Neural Systems for their paper: A. Deleforge, F. Forbes, and R. Horaud (2015), “Acoustic Space Learning for Sound-source Separation and Localization on Binaural Manifolds,” International Journal of …
May 24
(closed) PhD offer – Estimating the Geometry of Audio Scenes Using Virtually-Supervised Learning @ Inria Rennes
Details and application here
May 22
Paper + code on Compressive Spectral Clustering
Our paper on Compressive Spectral Clustering has been accepted to ICML. Read it on arXiv:1602.02018 or hal:hal-01320214 Download the code at http://cscbox.gforge.inria.fr
Apr 18
Available for download: FaµST code, to replace large dense matrices with computationally efficient approximations
FaµST (pronounce FAUST) yields computationnaly efficient approximations to large dense matrices that can speed up iterative solvers for large-scale linear inverse problems. See details on the methodology behind FaµST and some other applications, in our paper Le Magoarou L. and Gribonval R., « Flexible multi-layer sparse approximations of matrices and applications », Journal of Selected Topics in Signal …
Mar 03
Tout juste paru : numéro spécial de la revue « Traitement du Signal »
La revue « Traitement du Signal », publiée par Lavoisier sous l’égide de l’association GRETSI, paraît ce trimestre sous la forme d’un numéro spécial sur le thème « Traitement Des Signaux Musicaux : Multimodalité Et Nouvelles Interactions », sous la coordination de Nancy BERTIN, Frédéric BIMBOT, Jules ESPIAU DE LAMAËSTRE et Anaïk OLIVERO, membres et anciens membres de l’équipe PANAMA. …
Feb 26
(closed) Postdoc sur l’apprentissage statistique compressif @ Inria Rennes
The PANAMA team @ Inria, Rennes, France is seeking highly qualified post-doctoral candidates to contribute to the development of a general theoretic and algorithmic framework for compressive statistical learning, by leveraging concepts from compressive sensing and graph signal processing. Candidates should hold a Ph.D. in applied mathematics, statistics, theoretical computer science, or mathematical signal processing. …
