| Marginal likelihood computation for model selection and hypothesis testing: an extensive review F Llorente, L Martino, D Delgado, J Lopez-Santiago SIAM review 65 (1), 3-58, 2023 | 89 | 2023 |
| Patient no-show prediction: a systematic literature review D Carreras-García, D Delgado-Gómez, F Llorente-Fernández, ... Entropy 22 (6), 675, 2020 | 50 | 2020 |
| Adaptive quadrature schemes for Bayesian inference via active learning FL Fernández, L Martino, V Elvira, D Delgado, J López-Santiago IEEE Access 8, 208462-208483, 2020 | 22* | 2020 |
| A Survey of Monte Carlo Methods for Noisy and Costly Densities With Application to Reinforcement Learning and ABC F Llorente, L Martino, J Read, D Delgado‐Gómez International Statistical Review, 2024 | 18 | 2024 |
| Deep importance sampling based on regression for model inversion and emulation F Llorente, L Martino, D Delgado-Gómez, G Camps-Valls Digital Signal Processing 116, 103104, 2021 | 15 | 2021 |
| On the safe use of prior densities for Bayesian model selection F Llorente, L Martino, E Curbelo, J López‐Santiago, D Delgado Wiley Interdisciplinary Reviews: Computational Statistics 15 (1), e1595, 2023 | 14 | 2023 |
| MCMC‐driven importance samplers F Llorente, E Curbelo, L Martino, V Elvira, D Delgado Applied Mathematical Modelling 111, 310-331, 2022 | 14 | 2022 |
| Automatic tempered posterior distributions for Bayesian inversion problems L Martino, F Llorente, E Curbelo, J Lopez-Santiago, J Míguez Mathematics 9 (7), 784, 2021 | 14 | 2021 |
| Parallel metropolis–hastings coupler F Llorente, L Martino, D Delgado IEEE Signal Processing Letters 26 (6), 953-957, 2019 | 10 | 2019 |
| An exhaustive variable selection study for linear models of soundscape emotions: rankings and Gibbs analysis R San Millán-Castillo, L Martino, E Morgado, F Llorente IEEE/ACM Transactions on Audio, Speech, and Language Processing 30, 2460-2474, 2022 | 9 | 2022 |
| Optimality in noisy importance sampling F Llorente, L Martino, J Read, D Delgado-Gómez Signal Processing 194, 108455, 2022 | 9 | 2022 |
| On the computation of marginal likelihood via MCMC for model selection and hypothesis testing F Llorente, L Martino, D Delgado, J López-Santiago 2020 28th European Signal Processing Conference (EUSIPCO), 2373-2377, 2021 | 4 | 2021 |
| Target-aware Bayesian inference via generalized thermodynamic integration F Llorente, L Martino, D Delgado Computational Statistics 38 (4), 2097-2119, 2023 | 3 | 2023 |
| Fusion of Gaussian Processes Predictions with Monte Carlo Sampling M Ajirak, D Waxman, F Llorente, PM Djuric 2023 57th Asilomar Conference on Signals, Systems, and Computers, 1367-1371, 2023 | 1 | 2023 |
| Dynamic Random Feature Gaussian Processes for Bayesian Optimization of Time-Varying Functions F Llorente, PM Djurić ICASSP 2024-2024 IEEE International Conference on Acoustics, Speech and …, 2024 | | 2024 |
| Adaptive posterior distributions for covariance matrix learning in Bayesian inversion problems for multioutput signals L Martino, EA Curbelo Benitez, F Llorente Fernandez, D Delgado Gómez DES-Working Papers. Statistics and Econometrics. WS, 2023 | | 2023 |
| Adaptive posterior distributions for covariance matrix learning in Bayesian inversion problems for multioutput signals EA Curbelo Benitez, L Martino, F Llorente Fernandez, D Delgado Gómez | | 2023 |
| Adaptive posterior distributions for covariance matrix learning in Bayesian inversion problems for multioutput signals E Curbelo, L Martino, F Llorente, D Delgado-Gómez Statistics, 05, 2023 | | 2023 |
| Marginal likelihood computation for model selection and hypothesis testing: an extensive review F Llorente Fernández, L Martino, D Delgado Gómez, J López Santiago Society for Industrial and Applied Mathematics, 2023 | | 2023 |
| 8. MARGINAL LIKELIHOOD COMPUTATION FOR MODEL SELECTION AND HYPOTHESIS TESTING: AN EXTENSIVE S In, F Llorente, L Martino, D Delgado, J Lopez-Santiago Efficient Bayesian inference via Monte Carlo and machine learning algorithms …, 2022 | | 2022 |
Luca MartinoAssociate ProfessorVerified email at urjc.es
