gaussian process

AutoPrognosis: Automated Clinical Prognostic Modeling via Bayesian Optimization with Structured Kernel Learning ICML 2018 Batched Large-scale Bayesian Optimization in High-dimensional Spaces AISTATS 2018 Bayesian Alignments of Warped Multi-Output Gaussian Processes NeurIPS 2018 Bayesian Control of Large MDPs with Unknown Dynamics in Data-Poor Environments NeurIPS 2018 Bayesian Nonparametric Poisson-Process Allocation for Time-Sequence Modeling AISTATS 2018 Bayesian Nonparametric Spectral Estimation NeurIPS 2018 Bayesian Quadrature for Multiple Related Integrals ICML 2018 Bayesian Semi-supervised Learning with Graph Gaussian Processes NeurIPS 2018 Bayesian Structure Learning for Dynamic Brain Connectivity AISTATS 2018 BOCK : Bayesian Optimization with Cylindrical Kernels ICML 2018 Causal Inference and Mechanism Clustering of A Mixture of Additive Noise Models NeurIPS 2018 Conditional Neural Processes ICML 2018 Constant-Time Predictive Distributions for Gaussian Processes ICML 2018 Continuous-time Value Function Approximation in Reproducing Kernel Hilbert Spaces NeurIPS 2018 Data-Efficient Reinforcement Learning with Probabilistic Model Predictive Control AISTATS 2018 Deep Neural Networks as Gaussian Processes ICLR 2018 Demonstrating and Modelling Systematic Time-varying Annotator Disagreement in Continuous Emotion Annotation Interspeech 2018 Differentiable Compositional Kernel Learning for Gaussian Processes ICML 2018 Differentially Private Regression with Gaussian Processes AISTATS 2018 Differential networking with path weights in Gaussian trees PGM 2018 Dirichlet-based Gaussian Processes for Large-scale Calibrated Classification NeurIPS 2018 Efficient Bayesian Inference of Sigmoidal Gaussian Cox Processes JMLR 2018 Feature-correlation-aware Gaussian Process Latent Variable Model ACML 2018 Gaussian Process Behaviour in Wide Deep Neural Networks ICLR 2018 Gaussian Process Conditional Density Estimation NeurIPS 2018