Daniel Hernández-Lobato

86 papers A* 13A 1B 3C 2Misc 1Journal 51Unranked 14

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Improving the Linearized Laplace Approximation via Quadratic Approximations. CoRR Pedro Jiménez, Luis A. Ortega, Pablo Morales-Álvarez, Daniel Hernández-Lobato
2026	J	`jnl`	Robust multi-task boosting using clustering and local ensembling. CoRR Seyedsaman Emami, Daniel Hernández-Lobato, Gonzalo Martínez-Muñoz
2026	J	`jnl`	Robust-multi-task gradient boosting. Expert Syst. Appl. Seyedsaman Emami, Gonzalo Martínez-Muñoz, Daniel Hernández-Lobato
2026	J	`jnl`	Scalable Linearized Laplace Approximation via Surrogate Neural Kernel. CoRR Luis A. Ortega, Simón Rodríguez Santana, Daniel Hernández-Lobato
2025	J	`jnl`	Alpha entropy search for new information-based Bayesian optimization. Knowl. Based Syst. Daniel Fernández-Sánchez, Eduardo C. Garrido-Merchán, Daniel Hernández-Lobato
2025	J	`jnl`	Joint entropy search for multi-objective Bayesian optimization with constraints and multiple fidelities. Neurocomputing Daniel Fernández-Sánchez, Daniel Hernández-Lobato
2025	J	`jnl`	Robust-Multi-Task Gradient Boosting. CoRR Seyedsaman Emami, Gonzalo Martínez-Muñoz, Daniel Hernández-Lobato
2024	J	`jnl`	Alpha Entropy Search for New Information-based Bayesian Optimization. CoRR Daniel Fernández-Sánchez, Eduardo C. Garrido-Merchán, Daniel Hernández-Lobato
2024	J	`jnl`	Fixed-Mean Gaussian Processes for Post-hoc Bayesian Deep Learning. CoRR Luis A. Ortega, Simón Rodríguez Santana, Daniel Hernández-Lobato
2024	B	`conf`	Joint Entropy Search for Multi-objective Bayesian Optimization with Constraints and Multiple Fidelities. ESANN Daniel Fernández-Sánchez, Daniel Hernández-Lobato
2024	A*	`conf`	Variational Linearized Laplace Approximation for Bayesian Deep Learning. ICML Luis A. Ortega Andrés, Simón Rodríguez Santana, Daniel Hernández-Lobato
2023	J	`jnl`	Deep Transformed Gaussian Processes. CoRR Francisco Javier Sáez-Maldonado, Juan Maroñas, Daniel Hernández-Lobato
2023	A*	`conf`	Deep Variational Implicit Processes. ICLR Luis A. Ortega, Simón Rodríguez Santana, Daniel Hernández-Lobato
2023	A*	`conf`	Efficient Transformed Gaussian Processes for Non-Stationary Dependent Multi-class Classification. ICML Juan Maroñas, Daniel Hernández-Lobato
2023	J	`jnl`	Gaussian processes for missing value imputation. Knowl. Based Syst. Bahram Jafrasteh, Daniel Hernández-Lobato, Simón Pedro Lubián-López, Isabel Benavente-Fernández
2023	J	`jnl`	Improved max-value entropy search for multi-objective bayesian optimization with constraints. Neurocomputing Daniel Fernández-Sánchez, Eduardo C. Garrido-Merchán, Daniel Hernández-Lobato
2023	J	`jnl`	Inference over radiative transfer models using variational and expectation maximization methods. Mach. Learn. Daniel Heestermans Svendsen, Daniel Hernández-Lobato, Luca Martino, Valero Laparra, Álvaro Moreno-Martínez, Gustau Camps-Valls
2023	J	`jnl`	Parallel predictive entropy search for multi-objective Bayesian optimization with constraints applied to the tuning of machine learning algorithms. Expert Syst. Appl. Eduardo C. Garrido-Merchán, Daniel Fernández-Sánchez, Daniel Hernández-Lobato
2023	J	`jnl`	Variational Linearized Laplace Approximation for Bayesian Deep Learning. CoRR Luis A. Ortega, Simón Rodríguez Santana, Daniel Hernández-Lobato
2022	J	`jnl`	Adversarial α-divergence minimization for Bayesian approximate inference. Neurocomputing Simón Rodríguez Santana, Daniel Hernández-Lobato
2022	J	`jnl`	Alpha-divergence minimization for deep Gaussian processes. Int. J. Approx. Reason. Carlos Villacampa-Calvo, Gonzalo Hernández-Muñoz, Daniel Hernández-Lobato
2022	J	`jnl`	Correcting Model Bias with Sparse Implicit Processes. CoRR Simón Rodríguez Santana, Luis A. Ortega Andrés, Daniel Hernández-Lobato, Bryan Zaldivar
2022	J	`jnl`	Deep Variational Implicit Processes. CoRR Luis A. Ortega, Simón Rodríguez Santana, Daniel Hernández-Lobato
2022	J	`jnl`	Efficient Transformed Gaussian Processes for Non-Stationary Dependent Multi-class Classification. CoRR Juan Maroñas, Daniel Hernández-Lobato
2022	A*	`conf`	Function-space Inference with Sparse Implicit Processes. ICML Simón Rodríguez Santana, Bryan Zaldivar, Daniel Hernández-Lobato
2022	J	`jnl`	Gaussian Processes for Missing Value Imputation. CoRR Bahram Jafrasteh, Daniel Hernández-Lobato, Simón Pedro Lubián-López, Isabel Benavente-Fernández
2022	J	`jnl`	Inference over radiative transfer models using variational and expectation maximization methods. CoRR Daniel Heestermans Svendsen, Daniel Hernández-Lobato, Luca Martino, Valero Laparra, Álvaro Moreno, Gustau Camps-Valls
2022	A*	`conf`	Input Dependent Sparse Gaussian Processes. ICML Bahram Jafrasteh, Carlos Villacampa-Calvo, Daniel Hernández-Lobato
2021	A*	`conf`	Activation-level uncertainty in deep neural networks. ICLR Pablo Morales-Alvarez, Daniel Hernández-Lobato, Rafael Molina, José Miguel Hernández-Lobato
2021	J	`jnl`	Input Dependent Sparse Gaussian Processes. CoRR Bahram Jafrasteh, Carlos Villacampa-Calvo, Daniel Hernández-Lobato
2021	J	`jnl`	Multi-class Gaussian Process Classification with Noisy Inputs. J. Mach. Learn. Res. Carlos Villacampa-Calvo, Bryan Zaldivar, Eduardo C. Garrido-Merchán, Daniel Hernández-Lobato
2021	J	`jnl`	Sparse Implicit Processes for Approximate Inference. CoRR Simón Rodríguez Santana, Bryan Zaldivar, Daniel Hernández-Lobato
2020	J	`jnl`	Alpha divergence minimization in multi-class Gaussian process classification. Neurocomputing Carlos Villacampa-Calvo, Daniel Hernández-Lobato
2020	J	`jnl`	Dealing with categorical and integer-valued variables in Bayesian Optimization with Gaussian processes. Neurocomputing Eduardo C. Garrido-Merchán, Daniel Hernández-Lobato
2020	—	`conf`	Deep Gaussian Processes Using Expectation Propagation and Monte Carlo Methods. ECML/PKDD (3) Gonzalo Hernández-Muñoz, Carlos Villacampa-Calvo, Daniel Hernández-Lobato
2020	Misc	`conf`	Importance Weighted Adversarial Variational Bayes. HAIS Marta Gómez-Sancho, Daniel Hernández-Lobato
2020	J	`jnl`	Max-value Entropy Search for Multi-objective Bayesian Optimization with Constraints. CoRR Daniel Fernández-Sánchez, Eduardo C. Garrido-Merchán, Daniel Hernández-Lobato
2020	J	`jnl`	Multi-class Gaussian Process Classification with Noisy Inputs. CoRR Carlos Villacampa-Calvo, Bryan Zaldivar, Eduardo C. Garrido-Merchán, Daniel Hernández-Lobato
2020	J	`jnl`	Parallel Predictive Entropy Search for Multi-objective Bayesian Optimization with Constraints. CoRR Eduardo C. Garrido-Merchán, Daniel Hernández-Lobato
2019	J	`jnl`	Adversarial α-divergence Minimization for Bayesian Approximate Inference. CoRR Simón Rodríguez Santana, Daniel Hernández-Lobato
2019	—	`ch.`	Non-linear Causal Inference Using Gaussianity Measures. Cause Effect Pairs in Machine Learning Daniel Hernández-Lobato, Pablo Morales-Mombiela, David Lopez-Paz, Alberto Suárez
2019	J	`jnl`	Predictive Entropy Search for Multi-objective Bayesian Optimization with Constraints. Neurocomputing Eduardo C. Garrido-Merchán, Daniel Hernández-Lobato
2018	—	`conf`	Bayesian Optimization of the PC Algorithm for Learning Gaussian Bayesian Networks. CAEPIA Irene Córdoba, Eduardo C. Garrido-Merchán, Daniel Hernández-Lobato, Concha Bielza, Pedro Larrañaga
2018	J	`jnl`	Bayesian optimization of a hybrid system for robust ocean wave features prediction. Neurocomputing Laura Cornejo-Bueno, Eduardo C. Garrido-Merchán, Daniel Hernández-Lobato, Sancho Salcedo-Sanz
2018	J	`jnl`	Bayesian optimization of the PC algorithm for learning Gaussian Bayesian networks. CoRR Irene Córdoba-Sánchez, Eduardo C. Garrido-Merchán, Daniel Hernández-Lobato, Concha Bielza, Pedro Larrañaga
2018	J	`jnl`	Dealing with Categorical and Integer-valued Variables in Bayesian Optimization with Gaussian Processes. CoRR Eduardo C. Garrido-Merchán, Daniel Hernández-Lobato
2017	—	`conf`	Bayesian Optimization of a Hybrid Prediction System for Optimal Wave Energy Estimation Problems. IWANN (1) Laura Cornejo-Bueno, Eduardo C. Garrido-Merchán, Daniel Hernández-Lobato, Sancho Salcedo-Sanz
2017	A*	`conf`	Scalable Multi-Class Gaussian Process Classification using Expectation Propagation. ICML Carlos Villacampa-Calvo, Daniel Hernández-Lobato
2016	A*	`conf`	Ambiguity Helps: Classification with Disagreements in Crowdsourced Annotations. CVPR Viktoriia Sharmanska, Daniel Hernández-Lobato, José Miguel Hernández-Lobato, Novi Quadrianto
2016	A*	`conf`	Black-Box Alpha Divergence Minimization. ICML José Miguel Hernández-Lobato, Yingzhen Li, Mark Rowland, Thang D. Bui, Daniel Hernández-Lobato, Richard E. Turner
2016	A*	`conf`	Deep Gaussian Processes for Regression using Approximate Expectation Propagation. ICML Thang D. Bui, Daniel Hernández-Lobato, José Miguel Hernández-Lobato, Yingzhen Li, Richard E. Turner
2016	J	`jnl`	Deep Gaussian Processes for Regression using Approximate Expectation Propagation. CoRR Thang D. Bui, Daniel Hernández-Lobato, Yingzhen Li, José Miguel Hernández-Lobato, Richard E. Turner
2016	J	`jnl`	Non-linear Causal Inference using Gaussianity Measures. J. Mach. Learn. Res. Daniel Hernández-Lobato, Pablo Morales-Mombiela, David Lopez-Paz, Alberto Suárez
2016	A*	`conf`	Predictive Entropy Search for Multi-objective Bayesian Optimization. ICML Daniel Hernández-Lobato, José Miguel Hernández-Lobato, Amar Shah, Ryan P. Adams
2016	A	`conf`	Scalable Gaussian Process Classification via Expectation Propagation. AISTATS Daniel Hernández-Lobato, José Miguel Hernández-Lobato
2015	A*	`conf`	A Probabilistic Model for Dirty Multi-task Feature Selection. ICML Daniel Hernández-Lobato, José Miguel Hernández-Lobato, Zoubin Ghahramani
2015	J	`jnl`	Expectation propagation in linear regression models with spike-and-slab priors. Mach. Learn. José Miguel Hernández-Lobato, Daniel Hernández-Lobato, Alberto Suárez
2015	J	`jnl`	Special Issue on "Solving complex machine learning problems with ensemble methods". Neurocomputing Daniel Hernández-Lobato, Ioannis Katakis, Gonzalo Martínez-Muñoz, Ioannis Partalas
2014	J	`jnl`	A Double Pruning Scheme for Boosting Ensembles. IEEE Trans. Cybern. Víctor Soto, Sergio García-Moratilla, Gonzalo Martínez-Muñoz, Daniel Hernández-Lobato, Alberto Suárez
2014	—	`conf`	Mind the Nuisance: Gaussian Process Classification using Privileged Noise. NIPS Daniel Hernández-Lobato, Viktoriia Sharmanska, Kristian Kersting, Christoph H. Lampert, Novi Quadrianto
2014	J	`jnl`	Mind the Nuisance: Gaussian Process Classification using Privileged Noise. CoRR Daniel Hernández-Lobato, Viktoriia Sharmanska, Kristian Kersting, Christoph H. Lampert, Novi Quadrianto
2013	—	`conf`	Gaussian Process Conditional Copulas with Applications to Financial Time Series. NIPS José Miguel Hernández-Lobato, James Robert Lloyd, Daniel Hernández-Lobato
2013	J	`jnl`	Generalized spike-and-slab priors for Bayesian group feature selection using expectation propagation. J. Mach. Learn. Res. Daniel Hernández-Lobato, José Miguel Hernández-Lobato, Pierre Dupont
2013	J	`jnl`	How large should ensembles of classifiers be? Pattern Recognit. Daniel Hernández-Lobato, Gonzalo Martínez-Muñoz, Alberto Suárez
2013	—	`conf`	Learning Feature Selection Dependencies in Multi-task Learning. NIPS Daniel Hernández-Lobato, José Miguel Hernández-Lobato
2013	A*	`conf`	Statistical Tests for the Detection of the Arrow of Time in Vector Autoregressive Models. IJCAI Pablo Morales-Mombiela, Daniel Hernández-Lobato, Alberto Suárez
2012	B	`conf`	On the Independence of the Individual Predictions in Parallel Randomized Ensembles. ESANN Daniel Hernández-Lobato, Gonzalo Martínez-Muñoz, Alberto Suárez
2011	J	`jnl`	Empirical analysis and evaluation of approximate techniques for pruning regression bagging ensembles. Neurocomputing Daniel Hernández-Lobato, Gonzalo Martínez-Muñoz, Alberto Suárez
2011	J	`jnl`	Inference on the prediction of ensembles of infinite size. Pattern Recognit. Daniel Hernández-Lobato, Gonzalo Martínez-Muñoz, Alberto Suárez
2011	J	`jnl`	Network-based sparse Bayesian classification. Pattern Recognit. José Miguel Hernández-Lobato, Daniel Hernández-Lobato, Alberto Suárez
2011	—	`conf`	Robust Multi-Class Gaussian Process Classification. NIPS Daniel Hernández-Lobato, José Miguel Hernández-Lobato, Pierre Dupont
2010	—	`conf`	A Double Pruning Algorithm for Classification Ensembles. MCS Víctor Soto, Gonzalo Martínez-Muñoz, Daniel Hernández-Lobato, Alberto Suárez
2010	—	`conf`	Expectation Propagation for Bayesian Multi-task Feature Selection. ECML/PKDD (1) Daniel Hernández-Lobato, José Miguel Hernández-Lobato, Thibault Helleputte, Pierre Dupont
2010	J	`jnl`	Expectation Propagation for microarray data classification. Pattern Recognit. Lett. Daniel Hernández-Lobato, José Miguel Hernández-Lobato, Alberto Suárez
2009	J	`jnl`	An Analysis of Ensemble Pruning Techniques Based on Ordered Aggregation. IEEE Trans. Pattern Anal. Mach. Intell. Gonzalo Martínez-Muñoz, Daniel Hernández-Lobato, Alberto Suárez
2009	—	`conf`	Statistical Instance-Based Ensemble Pruning for Multi-class Problems. ICANN (1) Gonzalo Martínez-Muñoz, Daniel Hernández-Lobato, Alberto Suárez
2009	J	`jnl`	Statistical Instance-Based Pruning in Ensembles of Independent Classifiers. IEEE Trans. Pattern Anal. Mach. Intell. Daniel Hernández-Lobato, Gonzalo Martínez-Muñoz, Alberto Suárez
2008	J	`jnl`	Bayes Machines for binary classification. Pattern Recognit. Lett. Daniel Hernández-Lobato, José Miguel Hernández-Lobato
2008	J	`jnl`	Class-switching neural network ensembles. Neurocomputing Gonzalo Martínez-Muñoz, Aitor Sánchez-Martínez, Daniel Hernández-Lobato, Alberto Suárez
2008	—	`conf`	Sparse Bayes Machines for Binary Classification. ICANN (1) Daniel Hernández-Lobato
2007	—	`conf`	GARCH Processes with Non-parametric Innovations for Market Risk Estimation. ICANN (2) José Miguel Hernández-Lobato, Daniel Hernández-Lobato, Alberto Suárez
2007	C	`conf`	Out of Bootstrap Estimation of Generalization Error Curves in Bagging Ensembles. IDEAL Daniel Hernández-Lobato, Gonzalo Martínez-Muñoz, Alberto Suárez
2007	—	`conf`	Selection of Decision Stumps in Bagging Ensembles. ICANN (1) Gonzalo Martínez-Muñoz, Daniel Hernández-Lobato, Alberto Suárez
2006	—	`conf`	Building Ensembles of Neural Networks with Class-Switching. ICANN (1) Gonzalo Martínez-Muñoz, Aitor Sánchez-Martínez, Daniel Hernández-Lobato, Alberto Suárez
2006	C	`conf`	Pruning Adaptive Boosting Ensembles by Means of a Genetic Algorithm. IDEAL Daniel Hernández-Lobato, José Miguel Hernández-Lobato, Rubén Ruiz-Torrubiano, Ángel Valle
2006	B	`conf`	Pruning in Ordered Regression Bagging Ensembles. IJCNN Daniel Hernández-Lobato, Gonzalo Martínez-Muñoz, Alberto Suárez