predictive distribution

PACm-Bayes: Narrowing the Empirical Risk Gap in the Misspecified Bayesian Regime AISTATS 2022 Predictive variational Bayesian inference as risk-seeking optimization AISTATS 2022 The Neural Testbed: Evaluating Joint Predictions NeurIPS 2022 Estimating Uncertainty Intervals from Collaborating Networks JMLR 2021 Multi-class Gaussian Process Classification with Noisy Inputs JMLR 2021 Uncertainty-aware sensitivity analysis using Rényi divergences UAI 2021 Deep Sigma Point Processes UAI 2020 Healing Products of Gaussian Process Experts ICML 2020 On the Expressiveness of Approximate Inference in Bayesian Neural Networks NeurIPS 2020 Parametric Gaussian Process Regressors ICML 2020 Regularizing Class-Wise Predictions via Self-Knowledge Distillation CVPR 2020 Residual Neural Processes AAAI 2020 Can You Trust This Prediction? Auditing Pointwise Reliability After Learning AISTATS 2019 Subspace Inference for Bayesian Deep Learning UAI 2019 Constant-Time Predictive Distributions for Gaussian Processes ICML 2018 Coherent Probabilistic Forecasts for Hierarchical Time Series ICML 2017 A Unifying Framework of Anytime Sparse Gaussian Process Regression Models with Stochastic Variational Inference for Big Data ICML 2015 Bayesian Model Adaptation for Crowd Counts ICCV 2015 Predictive Entropy Search for Efficient Global Optimization of Black-box Functions NeurIPS 2014 Student-t Processes as Alternatives to Gaussian Processes AISTATS 2014 Posterior distributions are computable from predictive distributions AISTATS 2010 Adaptive Non-Stationary Kernel Regression for Terrain Modeling RSS 2007