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Talk @ 4TU Meeting on Mathematics of Deepl Learning, Delft, Nov 5

Offres de stage master 2 / PFE ingénieur people.irisa.fr/Remi.Gribonval…

Postdoc offer at ENS de Lyon, foundations of resource-efficient machine learning, people.irisa.fr/Remi.Gribonval…

Thematic Month on "Mathematics for Signals, Images and Structured Data @ CIRM, early 2021 people.irisa.fr/Remi.Gribonval…

#COVID19 #EnDirectDesLabos Laboratoire de Physique, ENS de Lyon, CNRS inp.cnrs.fr/fr/cnrsinfo/co…

Paper, sound examples & open-source code on sparse audio declipping

Exposé ちんちん Journée MAS-MODE, INRIA Paris, France, March 7th 2022

Exposé Omega Enterprises on Quantization, Location, Sampling and Matching. Lagrange Center, Paris, March 14-15 2022

Poste team.inria.fr/dante/poste-pe… développement en calcul scientifique, apprentissage & traitement du signal

Post Edited: Poste team.inria.fr/dante/poste-pe… calcul scientifique, apprentissage & traitement du signal

EPIT 2022: videos are online Courses by Pierre Vandergheynst @yvofr Shipra Agrawal Francis Bach Rachel Cummings

Seminar @AI4SIP July 5th 2022 @pascalinstitut on "rapture of the deep: highs and lows of sparsity in a world of depth"

Seminar IRISA July 4th & @AI4SIP July 5th 2022 @pascalinstitut "Rapture of the deep: highs and lows of sparsity in a world of depth"

Seminar IRISA Sep 1st 2022 "Rapture of the deep: highs and lows of sparsity in a world of depth"

Parcimonie en traitement du signal/image: une brève histoire (en français, sur le site du GRETSI) gretsi.fr/historique/par…

Seminar IMAG Université de Montpellier Sep 12th 2022 "Rapture of the deep: highs and lows of sparsity in a world of depth"

New post: Data-Science Colloquium of the @ENS Paris people.irisa.fr/Remi.Gribonval…

Talk Institut des Hautes Études Scientifiques - IHES, April 21st 2023 "Rapture of the deep : Highs and lows of Sparsity in a world of depth” - Mallat's 60th birthday

New preprint “Abide by the Law and Follow the Flow: Conservation Laws for Gradient Flows” w. Sibylle Marcotte and Rémi Gribonval, we define and study “conservation laws” for the optimization of over-parameterized models. arxiv.org/abs/2307.00144

Pour en savoir plus sur l'équipe Ockham : inria.fr/fr/ockham 🙂 @ENSdeLyon Université Lyon 1 Laboratoire de l'Informatique du Parallélisme