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Séminaire Image: Converge to optima without overparameterization – Rayleigh quotients and subnetwork tracking par David A. R. Robin
Séminaire Image: Converge to optima without overparameterization – Rayleigh quotients and subnetwork tracking par David A. R. Robin
Nous aurons le plaisir d'écouter David A. R. Robin , Postdoc au LAMSADE (Université Paris Dauphine). Il donnera un séminaire IMAGE le jeudi 1er octobre 2026 à 14h en salle de séminaire F-200. Titre : "Converge to optima without overparameterization - Rayleigh quotients and subnetwork tracking" Résumé : The Neural Tangent Kernel (NTK) is a … Continue reading Séminaire Image: Converge to optima without overparameterization – Rayleigh quotients and subnetwork tracking par David A. R. Robin
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Séminaire Image: Denoising image geometry, from sparse estimators to neural network denoisers par Nathanael Cuvelle–Magar
Séminaire Image: Denoising image geometry, from sparse estimators to neural network denoisers par Nathanael Cuvelle–Magar
Nous aurons le plaisir d'écouter Nathanael Cuvelle--Magar. Il donnera un séminaire IMAGE le jeudi 22 octobre 2026 à 14h en salle de séminaire F-200. Titre : "Denoising image geometry, from sparse estimators to neural network denoisers" Résumé : Denoising (white noise) has historically been a central task in signal processing, and is today at the … Continue reading Séminaire Image: Denoising image geometry, from sparse estimators to neural network denoisers par Nathanael Cuvelle–Magar
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