← Authors

Daniel Hernández-lobato

21 papers · 2011–2024 · 7 conferences · across top CS/AI conferences

Achievements

🏃 Academic Marathon (13) 🌈 Renaissance Researcher (5) 🐝 Cross-Pollinator (11) 🐣 Hot Topic Early Bird 🌉 Interdisciplinary Bridge 🌍 Conference Polyglot (7) 🗺️ Taxonomy Completionist (13) 🧭 Keyword Pioneer 🔬 Deep Specialist (10) 🏆 Keyword Champion (2) 🧬 Topic Evolution 🗃️ Keyword Collector (67) 🚀 Conference Pioneer 📈 Trend Setter 💎 Century Club (21) 🔥 Unstoppable (5) ⚡ Prolific Year (6)

Conferences

ICML (9) NIPS (4) JMLR (3) ICLR (2) AISTATS (1) CVPR (1) IJCAI (1)

Top co-authors

José Miguel Hernández-Lobato (7) Jose Hernandez-Lobato (3) Carlos Villacampa-Calvo (3) Luis A. Ortega (2) Yingzhen Li (2) Richard Turner (2) Alberto Suárez (2) Pablo Morales-Mombiela (2) Thang Bui (2) Novi Quadrianto (2)

Keywords

gaussian process (8) expectation propagation (8) variational inference (5) bayesian inference (5) approximate inference (4) multi-class classification (4) probabilistic modeling (4) multi-task learning (2) feature selection (2) gaussian process classification (2) privileged information (2) probabilistic model (2) sparse approximation (2) label noise (1) automatic differentiation (1) distributed learning (1) computer vision (1) robust classification (1) spike-and-slab prior (1) feature space (1)

Papers

Variational Linearized Laplace Approximation for Bayesian Deep Learning ICML 2024
Deep Variational Implicit Processes ICLR 2023
Efficient Transformed Gaussian Processes for Non-Stationary Dependent Multi-class Classification ICML 2023
Function-space Inference with Sparse Implicit Processes ICML 2022
Input Dependent Sparse Gaussian Processes ICML 2022
Activation-level uncertainty in deep neural networks ICLR 2021
Multi-class Gaussian Process Classification with Noisy Inputs JMLR 2021
Scalable Multi-Class Gaussian Process Classification using Expectation Propagation ICML 2017
Predictive Entropy Search for Multi-objective Bayesian Optimization ICML 2016
Scalable Gaussian Process Classification via Expectation Propagation AISTATS 2016
Ambiguity Helps: Classification With Disagreements in Crowdsourced Annotations CVPR 2016
Deep Gaussian Processes for Regression using Approximate Expectation Propagation ICML 2016
Black-Box Alpha Divergence Minimization ICML 2016
Non-linear Causal Inference using Gaussianity Measures JMLR 2016
A Probabilistic Model for Dirty Multi-task Feature Selection ICML 2015
Mind the Nuisance: Gaussian Process Classification using Privileged Noise NIPS 2014
Learning Feature Selection Dependencies in Multi-task Learning NIPS 2013
Statistical Tests for the Detection of the Arrow of Time in Vector Autoregressive Models IJCAI 2013
Generalized Spike-and-Slab Priors for Bayesian Group Feature Selection Using Expectation Propagation JMLR 2013
Gaussian Process Conditional Copulas with Applications to Financial Time Series NIPS 2013
Robust Multi-Class Gaussian Process Classification NIPS 2011