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gaussian process prior

21 papers

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gaussian process (1200) bayesian inference (1907) variational inference (2069) bayesian optimization (624) bayesian nonparametrics (270) latent variable model (564) nonparametric regression (111) markov chain monte carlo (725) stochastic gradient (296) reproduction number (2)

Papers

Tree Search-Based Evolutionary Bandits for Protein Sequence Optimization AAAI 2024
FSP-Laplace: Function-Space Priors for the Laplace Approximation in Bayesian Deep Learning NIPS 2024
Semiparametric Inference Using Fractional Posteriors JMLR 2023
Posterior Contraction for Deep Gaussian Process Priors JMLR 2023
Distributed Bayesian Varying Coefficient Modeling Using a Gaussian Process Prior JMLR 2022
Tracking Disease Outbreaks from Sparse Data with Bayesian Inference AAAI 2021
Raven's Progressive Matrices Completion with Latent Gaussian Process Priors 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
Gaussian Process Prior Variational Autoencoders NIPS 2018
AutoPrognosis: Automated Clinical Prognostic Modeling via Bayesian Optimization with Structured Kernel Learning ICML 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 NIPS 2014
Locally Adaptive Bayesian Multivariate Time Series NIPS 2013
Random function priors for exchangeable arrays with applications to graphs and relational data NIPS 2012
Switched Latent Force Models for Movement Segmentation NIPS 2010
Optimising Kernel Parameters and Regularisation Coefficients for Non-linear Discriminant Analysis JMLR 2006