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08/17/2023
Spectral information criterion for automatic elbow detection
We introduce a generalized information criterion that contains other wel...
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08/17/2023
Universal and Automatic Elbow Detection for Learning the Effective Number of Components in Model Selection Problems
We design a Universal Automatic Elbow Detector (UAED) for deciding the e...
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07/26/2022
An exhaustive variable selection study for linear models of soundscape emotions: rankings and Gibbs analysis
In the last decade, soundscapes have become one of the most active topic...
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06/10/2022
On the safe use of prior densities for Bayesian model selection
The application of Bayesian inference for the purpose of model selection...
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08/01/2021
A survey of Monte Carlo methods for noisy and costly densities with application to reinforcement learning
This survey gives an overview of Monte Carlo methodologies using surroga...
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07/25/2021
A Survey of Monte Carlo Methods for Parameter Estimation
Statistical signal processing applications usually require the estimatio...
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07/24/2021
Automatic tempered posterior distributions for Bayesian inversion problems
We propose a novel adaptive importance sampling scheme for Bayesian inve...
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05/06/2021
MCMC-driven importance samplers
Monte Carlo methods are the standard procedure for estimating complicate...
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10/20/2020
Deep Importance Sampling based on Regression for Model Inversion and Emulation
Understanding systems by forward and inverse modeling is a recurrent top...
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05/31/2020
Adaptive quadrature schemes for Bayesian inference via active learning
Numerical integration and emulation are fundamental topics across scient...
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04/10/2017
Group Importance Sampling for Particle Filtering and MCMC
Importance Sampling (IS) is a well-known Monte Carlo technique that appr...
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07/30/2015
Orthogonal parallel MCMC methods for sampling and optimization
Monte Carlo (MC) methods are widely used for Bayesian inference and opti...
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05/18/2015
Layered Adaptive Importance Sampling
Monte Carlo methods represent the "de facto" standard for approximating ...
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01/20/2015
Scalable Multi-Output Label Prediction: From Classifier Chains to Classifier Trellises
Multi-output inference tasks, such as multi-label classification, have b...
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08/17/2013
