gaussian process prior

FSP-Laplace: Function-Space Priors for the Laplace Approximation in Bayesian Deep Learning NeurIPS 2024 Tree Search-Based Evolutionary Bandits for Protein Sequence Optimization AAAI 2024 Posterior Contraction for Deep Gaussian Process Priors JMLR 2023 Semiparametric Inference Using Fractional Posteriors JMLR 2023 Distributed Bayesian Varying Coefficient Modeling Using a Gaussian Process Prior JMLR 2022 Raven's Progressive Matrices Completion with Latent Gaussian Process Priors AAAI 2021 Tracking Disease Outbreaks from Sparse Data with Bayesian Inference AAAI 2021 The Kalai-Smorodinsky solution for many-objective Bayesian optimization JMLR 2020 A Bayesian Perspective on the Deep Image Prior CVPR 2019 Multi-View Stereo by Temporal Nonparametric Fusion ICCV 2019 AutoPrognosis: Automated Clinical Prognostic Modeling via Bayesian Optimization with Structured Kernel Learning ICML 2018 Gaussian Process Prior Variational Autoencoders NeurIPS 2018 Variational Network Inference: Strong and Stable with Concrete Support ICML 2018 Bayesian Matrix Factorization with Non-Random Missing Data using Informative Gaussian Process Priors and Soft Evidences PGM 2016 Doubly Decomposing Nonparametric Tensor Regression ICML 2016 Optimal Bayesian Estimation in Random Covariate Design with a Rescaled Gaussian Process Prior JMLR 2015 PAC-Bayesian AUC classification and scoring NeurIPS 2014 Locally Adaptive Bayesian Multivariate Time Series NeurIPS 2013 Random function priors for exchangeable arrays with applications to graphs and relational data NeurIPS 2012 Switched Latent Force Models for Movement Segmentation NeurIPS 2010 Data Integration for Classification Problems Employing Gaussian Process Priors NeurIPS 2006 Optimising Kernel Parameters and Regularisation Coefficients for Non-linear Discriminant Analysis JMLR 2006