| The k-tied Normal Distribution: A Compact Parameterization of Gaussian Mean Field Posteriors in Bayesian Neural Networks | Feb 7, 2020 | Bayesian InferenceVariational Inference | —Unverified | 0 |
| Gaussian Variational State Estimation for Nonlinear State-Space Models | Feb 7, 2020 | State EstimationState Space Models | —Unverified | 0 |
| Conditional Deep Gaussian Processes: multi-fidelity kernel learning | Feb 7, 2020 | Few-Shot LearningGaussian Processes | CodeCode Available | 0 |
| Automatic structured variational inference | Feb 3, 2020 | Probabilistic ProgrammingVariational Inference | CodeCode Available | 0 |
| An Equivalence between Bayesian Priors and Penalties in Variational Inference | Feb 1, 2020 | Variational Inference | —Unverified | 0 |
| On Implicit Regularization in β-VAEs | Jan 31, 2020 | Variational Inference | —Unverified | 0 |
| On the Information Bottleneck Problems: Models, Connections, Applications and Information Theoretic Views | Jan 31, 2020 | Representation LearningVariational Inference | —Unverified | 0 |
| Multivariate Gaussian Variational Inference by Natural Gradient Descent | Jan 27, 2020 | Variational Inference | —Unverified | 0 |
| A Deep Learning Algorithm for High-Dimensional Exploratory Item Factor Analysis | Jan 22, 2020 | Computational EfficiencyVariational Inference | —Unverified | 0 |
| Newtonian Monte Carlo: single-site MCMC meets second-order gradient methods | Jan 15, 2020 | Second-order methodsVariational Inference | CodeCode Available | 0 |
