← Bayesian & Probabilistic
Machine Learning › Bayesian & Probabilistic ›

Gaussian Processes

568 directly classified papers

Papers per year

Papers

Hybrid Discriminative-Generative Approach with Gaussian Processes AISTATS 2014
Bayesian Logistic Gaussian Process Models for Dynamic Networks AISTATS 2014
Gaussian Process Volatility Model NIPS 2014
Incremental Local Gaussian Regression NIPS 2014
Mind the Nuisance: Gaussian Process Classification using Privileged Noise NIPS 2014
Distributed Variational Inference in Sparse Gaussian Process Regression and Latent Variable Models NIPS 2014
Fast Kernel Learning for Multidimensional Pattern Extrapolation NIPS 2014
Probabilistic ODE Solvers with Runge-Kutta Means NIPS 2014
Fast Allocation of Gaussian Process Experts ICML 2014
Automated Variational Inference for Gaussian Process Models NIPS 2014
Tree-structured Gaussian Process Approximations NIPS 2014
Variational Gaussian Process State-Space Models NIPS 2014
Gaussian Process Optimization with Mutual Information ICML 2014
Gaussian Process Classification and Active Learning with Multiple Annotators ICML 2014
Accelerating ABC methods using Gaussian processes AISTATS 2014
Nonmyopic ε-Bayes-Optimal Active Learning of Gaussian Processes ICML 2014
Sample Efficient Reinforcement Learning with Gaussian Processes ICML 2014
Active Learning for Multi-Objective Optimization ICML 2013
Bayesian Inference and Learning in Gaussian Process State-Space Models with Particle MCMC NIPS 2013
Efficient Optimization for Sparse Gaussian Process Regression NIPS 2013
It is all in the noise: Efficient multi-task Gaussian process inference with structured residuals NIPS 2013
Gaussian Process Conditional Copulas with Applications to Financial Time Series NIPS 2013
High-Dimensional Gaussian Process Bandits NIPS 2013
Bayesian optimization explains human active search NIPS 2013
Multi-Task Bayesian Optimization NIPS 2013