Fernando Llorente

Orcid: 0000-0003-4436-5709

Affiliations:
  • Stony Brook University, NY, USA
  • University Carlos III of Madrid, Leganés, Spain (former)


According to our database1, Fernando Llorente authored at least 16 papers between 2019 and 2023.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

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Links

Online presence:

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Bibliography

2023
Target-aware Bayesian inference via generalized thermodynamic integration.
Comput. Stat., December, 2023

Marginal Likelihood Computation for Model Selection and Hypothesis Testing: An Extensive Review.
SIAM Rev., February, 2023

FUSION OF GAUSSIAN PROCESSES PREDICTIONS WITH MONTE CARLO SAMPLING.
Proceedings of the 57th Asilomar Conference on Signals, Systems, and Computers, ACSSC 2023, Pacific Grove, CA, USA, October 29, 2023

2022
An Exhaustive Variable Selection Study for Linear Models of Soundscape Emotions: Rankings and Gibbs Analysis.
IEEE ACM Trans. Audio Speech Lang. Process., 2022

Optimality in noisy importance sampling.
Signal Process., 2022

Safe importance sampling based on partial posteriors and neural variational approximations.
Proceedings of the 30th European Signal Processing Conference, 2022

CAMEO: Curiosity Augmented Metropolis for Exploratory Optimal Policies.
Proceedings of the 30th European Signal Processing Conference, 2022

2021
Deep importance sampling based on regression for model inversion and emulation.
Digit. Signal Process., 2021

A survey of Monte Carlo methods for noisy and costly densities with application to reinforcement learning.
CoRR, 2021

Automatic tempered posterior distributions for Bayesian inversion problems.
CoRR, 2021

MCMC-driven importance samplers.
CoRR, 2021

A Nearest Neighbors Quadrature for Posterior Approximation via Adaptive Sequential Design.
Proceedings of the IEEE Statistical Signal Processing Workshop, 2021

2020
Patient No-Show Prediction: A Systematic Literature Review.
Entropy, 2020

Adaptive Quadrature Schemes for Bayesian Inference via Active Learning.
IEEE Access, 2020

On the computation of marginal likelihood via MCMC for model selection and hypothesis testing.
Proceedings of the 28th European Signal Processing Conference, 2020

2019
Parallel Metropolis-Hastings Coupler.
IEEE Signal Process. Lett., 2019


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