144 citations · 275 across the 9 of their papers we have counts for
10 papers
Nested Sampling: A Critical and Comprehensive Theoretical Guide
Luca Martino, Fernando Llorente
The nested sampling (NS) technique has gained widespread attention, particularly in cosmology and astronomy, due to its ability to efficiently explore high-likelihood regions - a f…
A unifying view of contrastive learning, importance sampling, and bridge sampling for energy-based models
Luca Martino
In the last decades, energy-based models (EBMs) have become an important class of probabilistic models in which a component of the likelihood is intractable and therefore cannot be…
An exhaustive variable selection study for linear models of soundscape emotions: rankings and Gibbs analysis
R. San Millán-Castillo, L. Martino, E. Morgado +1
In the last decade, soundscapes have become one of the most active topics in Acoustics, providing a holistic approach to the acoustic environment, which involves human perception a…
MCMC-driven importance samplers
F. Llorente, E. Curbelo, L. Martino +2
Monte Carlo sampling methods are the standard procedure for approximating complicated integrals of multidimensional posterior distributions in Bayesian inference. In this work, we…
Integrating Domain Knowledge in Data-driven Earth Observation with Process Convolutions
Daniel Heestermans Svendsen, Maria Piles, Jordi Muñoz-Marí +3
The modelling of Earth observation data is a challenging problem, typically approached by either purely mechanistic or purely data-driven methods. Mechanistic models encode the dom…
A likely magnetic activity cycle for the exoplanet host M dwarf GJ 3512
J. Lopez-Santiago, L. Martino, J. Miguez +1
Current radial velocity data from specialized instruments contain a large amount of information that may pass unnoticed if their analysis is not accurate. The joint use of Bayesian…
Probabilistic Regressor Chains with Monte Carlo Methods
Jesse Read, Luca Martino
A large number and diversity of techniques have been offered in the literature in recent years for solving multi-label classification tasks, including classifier chains where predi…
Rethinking the Effective Sample Size
Víctor Elvira, Luca Martino, Christian P. Robert
The effective sample size (ESS) is widely used in sample-based simulation methods for assessing the quality of a Monte Carlo approximation of a given distribution and of related in…
Generalized Multiple Importance Sampling
Víctor Elvira, Luca Martino, David Luengo +1
Importance Sampling methods are broadly used to approximate posterior distributions or some of their moments. In its standard approach, samples are drawn from a single proposal dis…
Two adaptive rejection sampling schemes for probability density functions log-convex tails
Luca Martino, Joaquín Míguez
Monte Carlo methods are often necessary for the implementation of optimal Bayesian estimators. A fundamental technique that can be used to generate samples from virtually any targe…