Fernando Llorente

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 22

Top Topics

Bayesian Inference

Top Venues

IEEE Signal Process. Lett.

Publications

Marzieh Ajirak, Daniel Waxman, Fernando Llorente, Petar M. Djuric
Fusion of Gaussian Processes Predictions with Monte Carlo Sampling. CoRR (2024)
Fernando Llorente, Petar M. Djuric
Dynamic Random Feature Gaussian Processes for Bayesian Optimization of Time-Varying Functions. ICASSP (2024)
Fernando Llorente, Luca Martino, David Delgado, Javier López-Santiago
Marginal Likelihood Computation for Model Selection and Hypothesis Testing: An Extensive Review. SIAM Rev. 65 (1) (2023)
Fernando Llorente, Luca Martino, David Delgado
Target-aware Bayesian inference via generalized thermodynamic integration. Comput. Stat. 38 (4) (2023)
Marzieh Ajirak, Daniel Waxman, Fernando Llorente, Petar M. Djuric
FUSION OF GAUSSIAN PROCESSES PREDICTIONS WITH MONTE CARLO SAMPLING. ACSSC (2023)
Roberto San Millán-Castillo, Luca Martino, Eduardo Morgado, Fernando Llorente
An Exhaustive Variable Selection Study for Linear Models of Soundscape Emotions: Rankings and Gibbs Analysis. IEEE ACM Trans. Audio Speech Lang. Process. 30 (2022)
Mohamed Alami Chehboune, Fernando Llorente, Rim Kaddah, Luca Martino, Jesse Read
CAMEO: Curiosity Augmented Metropolis for Exploratory Optimal Policies. CoRR (2022)
Fernando Llorente, Luca Martino, Jesse Read, David Delgado-Gómez
Optimality in noisy importance sampling. Signal Process. 194 (2022)
Fernando Llorente, Luca Martino, Jesse Read, David Delgado-Gómez
Optimality in Noisy Importance Sampling. CoRR (2022)
Fernando Llorente, Ernesto Curbelo, Luca Martino, Pablo M. Olmos, David Delgado
Safe importance sampling based on partial posteriors and neural variational approximations. EUSIPCO (2022)
Mohamed Alami Chehboune, Rim Kaddah, Luca Martino, Fernando Llorente, Jesse Read
CAMEO: Curiosity Augmented Metropolis for Exploratory Optimal Policies. EUSIPCO (2022)
Roberto San Millán-Castillo, Luca Martino, Eduardo Morgado, Fernando Llorente
An exhaustive variable selection study for linear models of soundscape emotions: rankings and Gibbs analysis. CoRR (2022)
Fernando Llorente, Luca Martino, David Delgado-Gómez, Gustavo Camps-Valls
Deep importance sampling based on regression for model inversion and emulation. Digit. Signal Process. 116 (2021)
Fernando Llorente, Luca Martino, Víctor Elvira, David Delgado
A Nearest Neighbors Quadrature for Posterior Approximation via Adaptive Sequential Design. SSP (2021)
Fernando Llorente, E. Curbelo, Luca Martino, Victor Elvira, David Delgado
MCMC-driven importance samplers. CoRR (2021)
Luca Martino, Fernando Llorente, E. Curbelo, Javier López-Santiago, Joaquín Míguez
Automatic tempered posterior distributions for Bayesian inversion problems. CoRR (2021)
Fernando Llorente, Luca Martino, Jessa Read, David Delgado
A survey of Monte Carlo methods for noisy and costly densities with application to reinforcement learning. CoRR (2021)
Fernando Llorente, Luca Martino, David Delgado, Javier López-Santiago
Marginal likelihood computation for model selection and hypothesis testing: an extensive review. CoRR (2020)
Fernando Llorente, Luca Martino, Víctor Elvira, David Delgado, Javier López-Santiago
Adaptive quadrature schemes for Bayesian inference via active learning. CoRR (2020)
Fernando Llorente, Luca Martino, David Delgado-Gómez, Javier López-Santiago
On the computation of marginal likelihood via MCMC for model selection and hypothesis testing. EUSIPCO (2020)
Fernando Llorente, Luca Martino, David Delgado, Gustau Camps-Valls
Deep Importance Sampling based on Regression for Model Inversion and Emulation. CoRR (2020)
Fernando Llorente, Luca Martino, David Delgado
Parallel Metropolis-Hastings Coupler. IEEE Signal Process. Lett. 26 (6) (2019)