19 citations · 37 across the 4 of their papers we have counts for
6 papers
On Last-Layer Algorithms for Classification: Decoupling Representation from Uncertainty Estimation
Nicolas Brosse, Carlos Riquelme, Alice Martin +2
Uncertainty quantification for deep learning is a challenging open problem. Bayesian statistics offer a mathematically grounded framework to reason about uncertainties; however, ap…
The promises and pitfalls of Stochastic Gradient Langevin Dynamics
Nicolas Brosse, Alain Durmus, Eric Moulines
Stochastic Gradient Langevin Dynamics (SGLD) has emerged as a key MCMC algorithm for Bayesian learning from large scale datasets. While SGLD with decreasing step sizes converges we…
Diffusion approximations and control variates for MCMC
Nicolas Brosse, Alain Durmus, Sean Meyn +2
A new methodology is presented for the construction of control variates to reduce the variance of additive functionals of Markov Chain Monte Carlo (MCMC) samplers. Our control vari…
Sampling from a log-concave distribution with compact support with proximal Langevin Monte Carlo
Nicolas Brosse, Alain Durmus, Éric Moulines +1
This paper presents a detailed theoretical analysis of the Langevin Monte Carlo sampling algorithm recently introduced in Durmus et al. (Efficient Bayesian computation by proximal…
Experimental study of a three dimensional cylinder-filament system
Nicolas Brosse, Carl Finmo, Fredrik Lundell +1
This experimental study reports on the behavior of a filament attached to the rear of a three- dimensional cylinder. The axis of the cylinder is placed normal to a uniform incoming…
Wake interaction of two disks falling in tandem
N. Brosse, S. Cazin, P. Ern
The fluid dynamics video illustrates the interaction of two disks falling in tandem at Reynolds number close to 100. Two fluorescent dyes were used to visualize the wake of each bo…