Daniel Hernández-Lobato
Universidad Autónoma de Madrid
H-index: 25
Europe-Spain
Top articles of Daniel Hernández-Lobato
Title | Journal | Author(s) | Publication Date |
|---|---|---|---|
Inference over radiative transfer models using variational and expectation maximization methods | Machine Learning | Daniel Heestermans Svendsen Daniel Hernandez-Lobato Luca Martino Valero Laparra Alvaro Moreno-Martinez | 2023/3 |
Deep Transformed Gaussian Processes | arXiv e-prints | Francisco Javier Sáez-Maldonado Juan Maroñas Daniel Hernández-Lobato | 2023/10 |
Gaussian processes for missing value imputation | Knowledge-Based Systems | Bahram Jafrasteh Daniel Hernández-Lobato Simón Pedro Lubián-López Isabel Benavente-Fernández | 2023/8/3 |
Variational Linearized Laplace Approximation for Bayesian Deep Learning | arXiv preprint arXiv:2302.12565 | Luis A Ortega Simón Rodríguez Santana Daniel Hernández-Lobato | 2023/2/24 |
Efficient transformed Gaussian processes for non-stationary dependent multi-class classification | Juan Maroñas Daniel Hernández-Lobato | 2023/7/3 | |
Parallel predictive entropy search for multi-objective Bayesian optimization with constraints applied to the tuning of machine learning algorithms | Expert Systems with Applications | Eduardo C Garrido-Merchán Daniel Fernández-Sánchez Daniel Hernández-Lobato | 2023/4/1 |
Correcting Model Bias with Sparse Implicit Processes | arXiv preprint arXiv:2207.10673 | Simón Rodríguez Santana Luis A Ortega Daniel Hernández-Lobato Bryan Zaldivar | 2022/7/21 |
Deep variational implicit processes | arXiv preprint arXiv:2206.06720 | Luis A Ortega Simón Rodríguez Santana Daniel Hernández-Lobato | 2022/6/14 |
Adversarial α-divergence minimization for Bayesian approximate inference | Neurocomputing | Simon Rodriguez-Santana Daniel Hernández-Lobato | 2022/1/30 |
Adversarial A-divergence minimization for Bayesian approximate inference | Simón Rodríguez Santana Daniel Hernández-Lobato | 2022 | |
Alpha-divergence minimization for deep Gaussian processes | International Journal of Approximate Reasoning | Carlos Villacampa-Calvo Gonzalo Hernández-Muñoz Daniel Hernández-Lobato | 2022/8 |
Input dependent sparse gaussian processes | Bahram Jafrasteh Carlos Villacampa-Calvo Daniel Hernández-Lobato | 2022 | |
Deep Gaussian processes using expectation propagation and Monte Carlo methods | Gonzalo Hernández-Muñoz Carlos Villacampa-Calvo Daniel Hernández-Lobato | 2020/7 | |
Multi-class gaussian process classification with noisy inputs | Journal of Machine Learning Research | Carlos Villacampa-Calvo Bryan Zaldívar Eduardo C Garrido-Merchán Daniel Hernández-Lobato | 2021 |
Function-space inference with sparse implicit processes | arXiv preprint arXiv:2110.07618 | Simón Rodríguez Santana Bryan Zaldivar Daniel Hernandez-Lobato | 2021/10/14 |
Dealing with categorical and integer-valued variables in bayesian optimization with gaussian processes | Neurocomputing | Eduardo C Garrido-Merchán Daniel Hernández-Lobato | 2020/3/7 |
Alpha divergence minimization in multi-class Gaussian process classification | Neurocomputing | Carlos Villacampa-Calvo Daniel Hernandez-Lobato | 2020/2/22 |
Importance Weighted Adversarial Variational Bayes | Marta Gómez-Sancho Daniel Hernández-Lobato | 2020/11/4 | |
Improved max-value entropy search for multi-objective bayesian optimization with constraints | Neurocomputing | Daniel Fernández-Sánchez Eduardo C Garrido-Merchán Daniel Hernández-Lobato | 2023/8/14 |
Activation-level uncertainty in deep neural networks | Pablo Morales-Alvarez Daniel Hernández-Lobato Rafael Molina José Miguel Hernández-Lobato | 2020/10/2 |
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