| Doubly Stochastic Variational Inference for Deep Gaussian Processes | May 24, 2017 | Gaussian ProcessesGeneral Classification | CodeCode Available | 0 | 5 |
| A Variational Approach to Bayesian Phylogenetic Inference | Apr 16, 2022 | Efficient ExplorationVariational Inference | CodeCode Available | 0 | 5 |
| DropMax: Adaptive Variational Softmax | Dec 21, 2017 | ClassificationGeneral Classification | CodeCode Available | 0 | 5 |
| Doubly Reparameterized Gradient Estimators for Monte Carlo Objectives | Oct 9, 2018 | Variational Inference | CodeCode Available | 0 | 5 |
| Dropout Inference in Bayesian Neural Networks with Alpha-divergences | Mar 8, 2017 | Variational Inference | CodeCode Available | 0 | 5 |
| Auxiliary Variational MCMC | May 1, 2019 | regressionVariational Inference | CodeCode Available | 0 | 5 |
| Amortized Variational Deep Q Network | Nov 3, 2020 | Deep Reinforcement LearningEfficient Exploration | CodeCode Available | 0 | 5 |
| Distributional Bayesian optimisation for variational inference on black-box simulators | Oct 16, 2019 | Bayesian OptimisationVariational Inference | CodeCode Available | 0 | 5 |
| Distributed Variational Inference for Online Supervised Learning | Sep 5, 2023 | Binary ClassificationVariational Inference | CodeCode Available | 0 | 5 |
| Distributed Variational Inference in Sparse Gaussian Process Regression and Latent Variable Models | Feb 6, 2014 | Dimensionality ReductionGaussian Processes | CodeCode Available | 0 | 5 |
