Bayesian Inference

Stochastic Proximal Langevin Algorithm: Potential Splitting and Nonasymptotic Rates NeurIPS 2019 Streaming Bayesian Inference for Crowdsourced Classification NeurIPS 2019 Striking the Right Balance With Uncertainty CVPR 2019 Structured Variational Inference in Continuous Cox Process Models NeurIPS 2019 Subspace Inference for Bayesian Deep Learning UAI 2019 Successor Uncertainties: Exploration and Uncertainty in Temporal Difference Learning NeurIPS 2019 Switching Linear Dynamics for Variational Bayes Filtering ICML 2019 Tensorial Change Analysis Using Probabilistic Tensor Regression AAAI 2019 Tensor Variable Elimination for Plated Factor Graphs ICML 2019 The 35th Uncertainty in Artificial Intelligence Conference: Preface UAI 2019 The Deep Weight Prior ICLR 2019 The Functional Neural Process NeurIPS 2019 The Gaussian Process Autoregressive Regression Model (GPAR) AISTATS 2019 The Implicit Metropolis-Hastings Algorithm NeurIPS 2019 The Kernel Interaction Trick: Fast Bayesian Discovery of Pairwise Interactions in High Dimensions ICML 2019 The Odds are Odd: A Statistical Test for Detecting Adversarial Examples ICML 2019 Theory of Minds: Understanding Behavior in Groups through Inverse Planning AAAI 2019 The pywmi Framework and Toolbox for Probabilistic Inference using Weighted Model Integration IJCAI 2019 The Randomized Midpoint Method for Log-Concave Sampling NeurIPS 2019 The Relative Complexity of Maximum Likelihood Estimation, MAP Estimation, and Sampling COLT 2019 The Thermodynamic Variational Objective NeurIPS 2019 The Variational Predictive Natural Gradient ICML 2019 Thompson Sampling and Approximate Inference NeurIPS 2019 Thompson Sampling Guided Stochastic Searching on the Line for Deceptive Environments with Applications to Root-Finding Problems JMLR 2019 Thompson Sampling on Symmetric Alpha-Stable Bandits IJCAI 2019