21 citations · 36 across the 8 of their papers we have counts for
3 papers · 1 filter
Monte Carlo guided Diffusion for Bayesian linear inverse problems
Gabriel Cardoso, Yazid Janati El Idrissi, Sylvain Le Corff +1
Ill-posed linear inverse problems arise frequently in various applications, from computational photography to medical imaging. A recent line of research exploits Bayesian inference…
Last layer state space model for representation learning and uncertainty quantification
Max Cohen, Maurice Charbit, Sylvain Le Corff
As sequential neural architectures become deeper and more complex, uncertainty estimation is more and more challenging. Efforts in quantifying uncertainty often rely on specific tr…
Variational latent discrete representation for time series modelling
Max Cohen, Maurice Charbit, Sylvain Le Corff
Discrete latent space models have recently achieved performance on par with their continuous counterparts in deep variational inference. While they still face various implementatio…