| Stein Variational Gradient Descent for Approximate Bayesian Computation | Oct 16, 2019 | Bayesian InferenceVariational Inference | —Unverified | 0 |
| Pseudo-Bayesian Learning via Direct Loss Minimization with Applications to Sparse Gaussian Process Models | Oct 16, 2019 | Variational Inference | —Unverified | 0 |
| Parametric Gaussian Process Regressors | Oct 16, 2019 | regressionVariational Inference | —Unverified | 0 |
| Global Approximate Inference via Local Linearisation for Temporal Gaussian Processes | Oct 16, 2019 | Bayesian InferenceGaussian Processes | —Unverified | 0 |
| Rapid Model Comparison by Amortizing Across Models | Oct 16, 2019 | modelTopic Models | CodeCode Available | 0 |
| Sequential Learning for Dirichlet Process Mixtures | Oct 16, 2019 | Variational Inference | —Unverified | 0 |
| Challenges in Computing and Optimizing Upper Bounds of Marginal Likelihood based on Chi-Square Divergences | Oct 16, 2019 | DiagnosticVariational Inference | —Unverified | 0 |
| Bijectors.jl: Flexible transformations for probability distributions | Oct 16, 2019 | Bayesian InferenceVariational Inference | CodeCode Available | 0 |
| Langevin Dynamics as Nonparametric Variational Inference | Oct 16, 2019 | Variational Inference | —Unverified | 0 |
| Interpretable User Models via Decision-rule Gaussian Processes: Preliminary Results on Energy Storage | Oct 16, 2019 | Bayesian InferenceGaussian Processes | —Unverified | 0 |