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gaussian process

1200 papers

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Also known as

GP

Co-occurring keywords

variational inference (2069) bayesian optimization (624) bayesian inference (1907) uncertainty quantification (1393) kernel methods (1097) gaussian processes (89) regret bound (1926) active learning (1301) sparse approximation (76) hyperparameter optimization (406)

Papers

Heavy-Tailed Process Priors for Selective Shrinkage NIPS 2010
Gaussian Process Preference Elicitation NIPS 2010
Multi-Task Learning using Generalized t Process AISTATS 2010
Dependent Indian Buffet Processes AISTATS 2010
Approximate parameter inference in a stochastic reaction-diffusion model AISTATS 2010
Gaussian processes with monotonicity information AISTATS 2010
Learning via Gaussian Herding NIPS 2010
Learning sparse dynamic linear systems using stable spline kernels and exponential hyperpriors NIPS 2010
Regret Bounds for Gaussian Process Bandit Problems AISTATS 2010
State-Space Inference and Learning with Gaussian Processes AISTATS 2010
Active Instance Sampling via Matrix Partition NIPS 2010
Dirichlet Process Mixtures of Generalized Linear Models AISTATS 2010
Bayesian Gaussian Process Latent Variable Model AISTATS 2010
Switched Latent Force Models for Movement Segmentation NIPS 2010
Identifying graph-structured activation patterns in networks NIPS 2010
Evaluation of Rarity of Fingerprints in Forensics NIPS 2010
Slice sampling covariance hyperparameters of latent Gaussian models NIPS 2010
Approximate inference in continuous time Gaussian-Jump processes NIPS 2010
Exact learning curves for Gaussian process regression on large random graphs NIPS 2010
Gaussian Processes for Machine Learning (GPML) Toolbox JMLR 2010
Elliptical slice sampling AISTATS 2010
Brain covariance selection: better individual functional connectivity models using population prior NIPS 2010
Implicitly Constrained Gaussian Process Regression for Monocular Non-Rigid Pose Estimation NIPS 2010
Variational Gaussian-process factor analysis for modeling spatio-temporal data NIPS 2009
Inter-domain Gaussian Processes for Sparse Inference using Inducing Features NIPS 2009