conftrace_

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

Stability of Controllers for Gaussian Process Forward Models ICML 2016
Computationally Efficient Bayesian Learning of Gaussian Process State Space Models AISTATS 2016
Extended and Unscented Kitchen Sinks ICML 2016
Integrating Topic Modeling with Word Embeddings by Mixtures of vMFs COLING 2016
Bayesian Leave-One-Out Cross-Validation Approximations for Gaussian Latent Variable Models JMLR 2016
Bayesian Policy Gradient and Actor-Critic Algorithms JMLR 2016
Threshold Learning for Optimal Decision Making NIPS 2016
A Fixed-Point Operator for Inference in Variational Bayesian Latent Gaussian Models AISTATS 2016
Estimating Nonlinear Neural Response Functions using GP Priors and Kronecker Methods NIPS 2016
Safe Exploration in Finite Markov Decision Processes with Gaussian Processes NIPS 2016
Stochastic Variational Deep Kernel Learning NIPS 2016
Unsupervised Stress Information Labeling Using Gaussian Process Latent Variable Model for Statistical Speech Synthesis INTERSPEECH 2016
Scalable Gaussian Processes for Characterizing Multidimensional Change Surfaces AISTATS 2016
Chained Gaussian Processes AISTATS 2016
Batch Bayesian Optimization via Local Penalization AISTATS 2016
Deep Kernel Learning AISTATS 2016
Time-Varying Gaussian Process Bandit Optimization AISTATS 2016
Scalable Gaussian Process Classification via Expectation Propagation AISTATS 2016
Gaussian Process Bandit Optimisation with Multi-fidelity Evaluations NIPS 2016
Observational-Interventional Priors for Dose-Response Learning NIPS 2016
Gaussian Processes for Survival Analysis NIPS 2016
What's Wrong With That Object? Identifying Images of Unusual Objects by Modelling the Detection Score Distribution CVPR 2016
Scalable Structure Discovery in Regression using Gaussian Processes AUTOML 2016
Probabilistic Linear Multistep Methods NIPS 2016
A scalable end-to-end Gaussian process adapter for irregularly sampled time series classification NIPS 2016