gaussian process

Instance Dependent Regret Analysis of Kernelized Bandits ICML 2022 Joint Entropy Search For Maximally-Informed Bayesian Optimization NeurIPS 2022 Jump Gaussian Process Model for Estimating Piecewise Continuous Regression Functions JMLR 2022 Kernel Interpolation with Sparse Grids NeurIPS 2022 Laplace approximated Gaussian process state-space models UAI 2022 Learning Curves for Gaussian Process Regression with Power-Law Priors and Targets ICLR 2022 Learning Fractional White Noises in Neural Stochastic Differential Equations NeurIPS 2022 Learning Inconsistent Preferences with Gaussian Processes AISTATS 2022 Learning interacting dynamical systems with latent Gaussian process ODEs NeurIPS 2022 Learning invariant weights in neural networks UAI 2022 Learning Structured Gaussians To Approximate Deep Ensembles CVPR 2022 Learning Temporal Evolution of Spatial Dependence with Generalized Spatiotemporal Gaussian Process Models JMLR 2022 Log-Linear-Time Gaussian Processes Using Binary Tree Kernels NeurIPS 2022 Low-precision arithmetic for fast Gaussian processes UAI 2022 Marginalising over Stationary Kernels with Bayesian Quadrature AISTATS 2022 Measuring the robustness of Gaussian processes to kernel choice AISTATS 2022 Modeling the Machine Learning Multiverse NeurIPS 2022 Modelling Non-Smooth Signals with Complex Spectral Structure AISTATS 2022 Monte Carlo Tree Descent for Black-Box Optimization NeurIPS 2022 Movement Penalized Bayesian Optimization with Application to Wind Energy Systems NeurIPS 2022 Multi-fidelity Monte Carlo: a pseudo-marginal approach NeurIPS 2022 Multiple Imputation with Neural Network Gaussian Process for High-dimensional Incomplete Data ACML 2022 Multi-Relational Graph Representation Learning with Bayesian Gaussian Process Network AAAI 2022 Natural image synthesis for the retina with variational information bottleneck representation NeurIPS 2022 NeuralEF: Deconstructing Kernels by Deep Neural Networks ICML 2022