variational inference

Specifying Weight Priors in Bayesian Deep Neural Networks with Empirical Bayes AAAI 2020 Spike and slab variational Bayes for high dimensional logistic regression NeurIPS 2020 State Space Expectation Propagation: Efficient Inference Schemes for Temporal Gaussian Processes ICML 2020 Stein Variational Model Predictive Control CoRL 2020 Stochastic Convolutional Recurrent Networks for Language Modeling Interspeech 2020 Stochastic Deep Gaussian Processes over Graphs NeurIPS 2020 Stochastic Differential Equations with Variational Wishart Diffusions ICML 2020 Stochastic Latent Residual Video Prediction ICML 2020 Stochastic Neural Network with Kronecker Flow AISTATS 2020 Stochastic Particle-Optimization Sampling and the Non-Asymptotic Convergence Theory AISTATS 2020 Stochastic Variational Inference for Dynamic Correlated Topic Models UAI 2020 Streaming Nonlinear Bayesian Tensor Decomposition UAI 2020 Streamlined Variational Inference with Higher Level Random Effects JMLR 2020 Structured Probabilistic End-to-End Learning from Crowds IJCAI 2020 Structured Variational Inference in Partially Observable Unstable Gaussian Process State Space Models L4DC 2020 SUMO: Unbiased Estimation of Log Marginal Probability for Latent Variable Models ICLR 2020 SVGD as a kernelized Wasserstein gradient flow of the chi-squared divergence NeurIPS 2020 SVQN: Sequential Variational Soft Q-Learning Networks ICLR 2020 Switching Poisson Gamma Dynamical Systems IJCAI 2020 Target–Aware Bayesian Inference: How to Beat Optimal Conventional Estimators JMLR 2020 Task-Agnostic Online Reinforcement Learning with an Infinite Mixture of Gaussian Processes NeurIPS 2020 Temporal Positive-unlabeled Learning for Biomedical Hypothesis Generation via Risk Estimation NeurIPS 2020 The Hawkes Edge Partition Model for Continuous-time Event-based Temporal Networks UAI 2020 The Indian Chefs Process UAI 2020 The k-tied Normal Distribution: A Compact Parameterization of Gaussian Mean Field Posteriors in Bayesian Neural Networks ICML 2020