Publications (36)
Variational Linearized Laplace Approximation for Bayesian Deep Learning
Luis A. Ortega, Simón RodrÃguez Santana, Daniel Hernández-Lobato
Dealing with Integer-valued Variables in Bayesian Optimization with Gaussian Processes
Eduardo C. Garrido-Merchán, Daniel Hernández-Lobato
Robust-Multi-Task Gradient Boosting
Seyedsaman Emami, Gonzalo MartÃnez-Muñoz, Daniel Hernández-Lobato
Alpha Entropy Search for New Information-based Bayesian Optimization
Daniel Fernández-Sánchez, Eduardo C. Garrido-Merchán, Daniel Hernández-Lobato
Predictive Entropy Search for Multi-objective Bayesian Optimization with Constraints
Eduardo C. Garrido-Merchán, Daniel Hernández-Lobato
Mind the Nuisance: Gaussian Process Classification using Privileged Noise
Daniel Hernández-Lobato, Viktoriia Sharmanska, Kristian Kersting +2
Robust multi-task boosting using clustering and local ensembling
Seyedsaman Emami, Daniel Hernández-Lobato, Gonzalo MartÃnez-Muñoz
Training Deep Gaussian Processes using Stochastic Expectation Propagation and Probabilistic Backpropagation
Thang D. Bui, José Miguel Hernández-Lobato, Yingzhen Li +2
Conditional Diffusion Sampling
Francisco M. Castro-MacÃas, Pablo Morales-Ãlvarez, Saifuddin Syed +3
Correcting Model Bias with Sparse Implicit Processes
Simón RodrÃguez Santana, Luis A. Ortega, Daniel Hernández-Lobato +1
Convergent Expectation Propagation in Linear Models with Spike-and-slab Priors
José Miguel Hernández-Lobato, Daniel Hernández-Lobato
Parallel Predictive Entropy Search for Multi-objective Bayesian Optimization with Constraints
Eduardo C. Garrido-Merchán, Daniel Hernández-Lobato
Deep Gaussian Processes for Regression using Approximate Expectation Propagation
Thang D. Bui, Daniel Hernández-Lobato, Yingzhen Li +2
Inference over radiative transfer models using variational and expectation maximization methods
Daniel Heestermans Svendsen, Daniel Hernández-Lobato, Luca Martino +3
Improving the Linearized Laplace Approximation via Quadratic Approximations
Pedro Jiménez, Luis A. Ortega, Pablo Morales-Ãlvarez +1
Scalable Gaussian Process Classification via Expectation Propagation
Daniel Hernández-Lobato, José Miguel Hernández-Lobato
Improved Max-value Entropy Search for Multi-objective Bayesian Optimization with Constraints
Daniel Fernández-Sánchez, Eduardo C. Garrido-Merchán, Daniel Hernández-Lobato
Stochastic Expectation Propagation for Large Scale Gaussian Process Classification
Daniel Hernández-Lobato, José Miguel Hernández-Lobato, Yingzhen Li +2
Gaussian Process Conditional Copulas with Applications to Financial Time Series
José Miguel Hernández-Lobato, James Robert Lloyd, Daniel Hernández-Lobato
Gaussian Processes for Missing Value Imputation
Bahram Jafrasteh, Daniel Hernández-Lobato, Simón Pedro Lubián-López +1
Scalable Multi-Class Gaussian Process Classification using Expectation Propagation
Carlos Villacampa-Calvo, Daniel Hernández-Lobato
Fixed-Mean Gaussian Processes for Post-hoc Bayesian Deep Learning
Luis A. Ortega, Simón RodrÃguez-Santana, Daniel Hernández-Lobato
Input Dependent Sparse Gaussian Processes
Bahram Jafrasteh, Carlos Villacampa-Calvo, Daniel Hernández-Lobato
Bayesian optimization of the PC algorithm for learning Gaussian Bayesian networks
Irene Córdoba, Eduardo C. Garrido-Merchán, Daniel Hernández-Lobato +2
Efficient Transformed Gaussian Processes for Non-Stationary Dependent Multi-class Classification
Juan Maroñas, Daniel Hernández-Lobato
Multi-class Gaussian Process Classification with Noisy Inputs
Carlos Villacampa-Calvo, Bryan Zaldivar, Eduardo C. Garrido-Merchán +1
Deep Variational Implicit Processes
Luis A. Ortega, Simón RodrÃguez Santana, Daniel Hernández-Lobato
Black-box $α$-divergence Minimization
José Miguel Hernández-Lobato, Yingzhen Li, Mark Rowland +3
Dealing with Categorical and Integer-valued Variables in Bayesian Optimization with Gaussian Processes
Eduardo C. Garrido-Merchán, Daniel Hernández-Lobato
Deep Transformed Gaussian Processes
Francisco Javier Sáez-Maldonado, Juan Maroñas, Daniel Hernández-Lobato
Non-linear Causal Inference using Gaussianity Measures
Daniel Hernández-Lobato, Pablo Morales-Mombiela, David Lopez-Paz +1
Scalable Linearized Laplace Approximation via Surrogate Neural Kernel
Luis A. Ortega, Simón RodrÃguez-Santana, Daniel Hernández-Lobato
An Analysis of Posterior Collapse, Parameterization and Initialization in Variational Deep Gaussian Processes
Francisco Javier Sáez-Maldonado, Juan Maroñas, Daniel Hernández-Lobato
Adversarial $α$-divergence Minimization for Bayesian Approximate Inference
Simón RodrÃguez Santana, Daniel Hernández-Lobato
Function-space Inference with Sparse Implicit Processes
Simón RodrÃguez Santana, Bryan Zaldivar, Daniel Hernández-Lobato
Predictive Entropy Search for Multi-objective Bayesian Optimization
Daniel Hernández-Lobato, José Miguel Hernández-Lobato, Amar Shah +1