posterior distribution

Fast-rate PAC-Bayes Generalization Bounds via Shifted Rademacher Processes NeurIPS 2019 Hamiltonian Monte Carlo with Energy Conserving Subsampling JMLR 2019 Learning Hawkes Processes from a handful of events NeurIPS 2019 Marginal Posterior Sampling for Slate Bandits IJCAI 2019 Optimal PAC-Bayesian Posteriors for Stochastic Classifiers and their use for Choice of SVM Regularization Parameter ACML 2019 Orthogonality-Promoting Dictionary Learning via Bayesian Inference AAAI 2019 Projected Stein Variational Newton: A Fast and Scalable Bayesian Inference Method in High Dimensions NeurIPS 2019 Pseudo-Extended Markov chain Monte Carlo NeurIPS 2019 Rotation Invariant Householder Parameterization for Bayesian PCA ICML 2019 Scalable Thompson Sampling via Optimal Transport AISTATS 2019 Topic-Guided Variational Auto-Encoder for Text Generation NAACL 2019 Unsupervised Visual Domain Adaptation: A Deep Max-Margin Gaussian Process Approach CVPR 2019 Variational Autoencoder with Implicit Optimal Priors AAAI 2019 Variational Bayes under Model Misspecification NeurIPS 2019 A Bayesian Nonparametric View on Count-Min Sketch NeurIPS 2018 Adversarial Distillation of Bayesian Neural Network Posteriors ICML 2018 Analytic solution and stationary phase approximation for the Bayesian lasso and elastic net NeurIPS 2018 A probabilistic population code based on neural samples NeurIPS 2018 A Scalable Laplace Approximation for Neural Networks ICLR 2018 Bayesian Adversarial Learning NeurIPS 2018 Bayesian Nonparametric Spectral Estimation NeurIPS 2018 Bayesian Quadrature for Multiple Related Integrals ICML 2018 Bayesian Tactile Exploration for Compliant Docking With Uncertain Shapes RSS 2018 Data-dependent PAC-Bayes priors via differential privacy NeurIPS 2018 Inference in Deep Gaussian Processes using Stochastic Gradient Hamiltonian Monte Carlo NeurIPS 2018