posterior distribution

Probabilistic Safety for Bayesian Neural Networks UAI 2020 Radial and Directional Posteriors for Bayesian Deep Learning AAAI 2020 Replica-Exchange Nos\'e-Hoover Dynamics for Bayesian Learning on Large Datasets NeurIPS 2020 Sampling-Free Learning of Bayesian Quantized Neural Networks ICLR 2020 Source Separation with Deep Generative Priors ICML 2020 Stein Variational Model Predictive Control CoRL 2020 Target–Aware Bayesian Inference: How to Beat Optimal Conventional Estimators JMLR 2020 The k-tied Normal Distribution: A Compact Parameterization of Gaussian Mean Field Posteriors in Bayesian Neural Networks ICML 2020 Towards Consistent Variational Auto-Encoding (Student Abstract) AAAI 2020 Uncertainty Quantification for Sparse Deep Learning AISTATS 2020 Unlabelled Data Improves Bayesian Uncertainty Calibration under Covariate Shift ICML 2020 Accelerate CNN via Recursive Bayesian Pruning ICCV 2019 Adding Constraints to Bayesian Inverse Problems AAAI 2019 Adv-BNN: Improved Adversarial Defense through Robust Bayesian Neural Network ICLR 2019 Amortized Monte Carlo Integration ICML 2019 Analyzing Inverse Problems with Invertible Neural Networks ICLR 2019 A Particle-Based Variational Approach to Bayesian Non-negative Matrix Factorization JMLR 2019 Attentive State-Space Modeling of Disease Progression NeurIPS 2019 Bayesian Policy Optimization for Model Uncertainty ICLR 2019 BayesSim: Adaptive Domain Randomization Via Probabilistic Inference for Robotics Simulators RSS 2019 Bayes Test of Precision, Recall, and F1 Measure for Comparison of Two Natural Language Processing Models ACL 2019 Data-Distortion Guided Self-Distillation for Deep Neural Networks AAAI 2019 Dense Depth Posterior (DDP) From Single Image and Sparse Range CVPR 2019 Differentially Private Bayesian Linear Regression NeurIPS 2019 Evaluating Topic Quality with Posterior Variability EMNLP 2019