4 papers
Beyond MMSE: Enhancing PnP Restoration with ProxiMAP
Kenta Vert, Giacomo Meanti, Scott Pesme +2
Plug-and-Play (PnP) methods have become standard tools for solving imaging inverse problems by replacing the intractable maximum a posteriori (MAP) denoiser with the MMSE one. Whil…
MAP Estimation with Denoisers: Convergence Rates and Guarantees
Scott Pesme, Giacomo Meanti, Michael Arbel +1
Denoiser models have become powerful tools for inverse problems, enabling the use of pretrained networks to approximate the score of a smoothed prior distribution. These models are…
A Theoretical Framework for Grokking: Interpolation followed by Riemannian Norm Minimisation
Etienne Boursier, Scott Pesme, Radu-Alexandru Dragomir
We study the dynamics of gradient flow with small weight decay on general training losses . Under mild regularity assumptions and assuming convergen…
Implicit Bias of Mirror Flow on Separable Data
Scott Pesme, Radu-Alexandru Dragomir, Nicolas Flammarion
We examine the continuous-time counterpart of mirror descent, namely mirror flow, on classification problems which are linearly separable. Such problems are minimised `at infinity'…