203 citations · 2.2k across the 52 of their papers we have counts for
6 papers · 1 filter
Polycrystalline MnBi as a transverse thermoelectric material
Alessandro Sola, Elena Olivetti, Luca Martino +1
To assess the potential of polycrystalline MnBi as a transverse thermoelectric material, we have experimentally investigated its anomalous Nernst effect (ANE) by means of the heat…
Gradient-based Adaptive Importance Samplers
Víctor Elvira, Emilie Chouzenoux, Ömer Deniz Akyildiz +1
Importance sampling (IS) is a powerful Monte Carlo methodology for the approximation of intractable integrals, very often involving a target probability density function. The perfo…
On the safe use of prior densities for Bayesian model selection
F. Llorente, L. Martino, E. Curbelo +2
The application of Bayesian inference for the purpose of model selection is very popular nowadays. In this framework, models are compared through their marginal likelihoods, or the…
CAMEO: Curiosity Augmented Metropolis for Exploratory Optimal Policies
Simo Alami. C, Fernando Llorente, Rim Kaddah +2
Reinforcement Learning has drawn huge interest as a tool for solving optimal control problems. Solving a given problem (task or environment) involves converging towards an optimal…
Inference over radiative transfer models using variational and expectation maximization methods
Daniel Heestermans Svendsen, Daniel Hernández-Lobato, Luca Martino +3
Earth observation from satellites offers the possibility to monitor our planet with unprecedented accuracy. Radiative transfer models (RTMs) encode the energy transfer through the…
Optimality in Noisy Importance Sampling
Fernando Llorente, Luca Martino, Jesse Read +1
In this work, we analyze the noisy importance sampling (IS), i.e., IS working with noisy evaluations of the target density. We present the general framework and derive optimal prop…