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Gaussian Processes

568 directly classified papers

Papers per year

Papers

A Mutually-Dependent Hadamard Kernel for Modelling Latent Variable Couplings ACML 2017
Identification of Gaussian Process State Space Models NIPS 2017
Spectral Mixture Kernels for Multi-Output Gaussian Processes NIPS 2017
Data-Efficient Reinforcement Learning in Continuous State-Action Gaussian-POMDPs NIPS 2017
Bayesian Inference of Individualized Treatment Effects using Multi-task Gaussian Processes NIPS 2017
Linearly constrained Gaussian processes NIPS 2017
Safe Model-based Reinforcement Learning with Stability Guarantees NIPS 2017
Bayesian Leave-One-Out Cross-Validation Approximations for Gaussian Latent Variable Models JMLR 2016
A scalable end-to-end Gaussian process adapter for irregularly sampled time series classification NIPS 2016
What's Wrong With That Object? Identifying Images of Unusual Objects by Modelling the Detection Score Distribution CVPR 2016
e-PAL: An Active Learning Approach to the Multi-Objective Optimization Problem JMLR 2016
Estimating Nonlinear Neural Response Functions using GP Priors and Kronecker Methods NIPS 2016
Incremental Variational Sparse Gaussian Process Regression NIPS 2016
Voice Conversion Based on Matrix Variate Gaussian Mixture Model Using Multiple Frame Features INTERSPEECH 2016
Acoustic-to-Articulatory Inversion Mapping Based on Latent Trajectory Gaussian Mixture Model INTERSPEECH 2016
Efficient Computation of Gaussian Process Regression for Large Spatial Data Sets by Patching Local Gaussian Processes JMLR 2016
Probabilistic Linear Multistep Methods NIPS 2016
A Fixed-Point Operator for Inference in Variational Bayesian Latent Gaussian Models AISTATS 2016
Safe Exploration in Finite Markov Decision Processes with Gaussian Processes NIPS 2016
Bayesian Matrix Factorization with Non-Random Missing Data using Informative Gaussian Process Priors and Soft Evidences PGM 2016
Multi-task Sparse Structure Learning with Gaussian Copula Models JMLR 2016
Gaussian process nonparametric tensor estimator and its minimax optimality ICML 2016
Kernel Observers: Systems-Theoretic Modeling and Inference of Spatiotemporally Evolving Processes NIPS 2016
Gaussian Process Bandit Optimisation with Multi-fidelity Evaluations NIPS 2016
On Quantile Regression in Reproducing Kernel Hilbert Spaces with the Data Sparsity Constraint JMLR 2016