Gaussian Processes

A Learnable Safety Measure CoRL 2019 Banded Matrix Operators for Gaussian Markov Models in the Automatic Differentiation Era AISTATS 2019 Band-Limited Gaussian Processes: The Sinc Kernel NeurIPS 2019 Bayesian Layers: A Module for Neural Network Uncertainty NeurIPS 2019 Bayesian Optimization under Heavy-tailed Payoffs NeurIPS 2019 Bayesian Optimization with Binary Auxiliary Information UAI 2019 Calibrating Deep Convolutional Gaussian Processes AISTATS 2019 Change Surfaces for Expressive Multidimensional Changepoints and Counterfactual Prediction JMLR 2019 Collective Online Learning of Gaussian Processes in Massive Multi-Agent Systems AAAI 2019 Deeper Connections between Neural Networks and Gaussian Processes Speed-up Active Learning IJCAI 2019 Deep learning with differential Gaussian process flows AISTATS 2019 Efficient Gaussian Process Classification Using Pólya-Gamma Data Augmentation AAAI 2019 Efficient Inference in Multi-task Cox Process Models AISTATS 2019 Efficient Neutrino Oscillation Parameter Inference with Gaussian Process AAAI 2019 Embarrassingly Parallel Inference for Gaussian Processes JMLR 2019 Exact Gaussian Processes on a Million Data Points NeurIPS 2019 Expressive Priors in Bayesian Neural Networks: Kernel Combinations and Periodic Functions UAI 2019 Gaussian Processes with Linear Operator Inequality Constraints JMLR 2019 Gaussian Process Models of Sound Change in Indo-Aryan Dialectology ACL 2019 Generic Inference in Latent Gaussian Process Models JMLR 2019 Hyperparameter Learning via Distributional Transfer NeurIPS 2019 Learning from demonstration with model-based Gaussian process CoRL 2019 Learning interpretable continuous-time models of latent stochastic dynamical systems ICML 2019 Maximum Likelihood for Gaussian Process Classification and Generalized Linear Mixed Models under Case-Control Sampling JMLR 2019 Modelling Uncertainty in Collaborative Document Quality Assessment EMNLP 2019