| Learning to infer in recurrent biological networks | Jun 18, 2020 | Bayesian InferenceVariational Inference | CodeCode Available | 0 | 5 |
| Doubly Reparameterized Gradient Estimators for Monte Carlo Objectives | Oct 9, 2018 | Variational Inference | CodeCode Available | 0 | 5 |
| DropMax: Adaptive Variational Softmax | Dec 21, 2017 | ClassificationGeneral Classification | CodeCode Available | 0 | 5 |
| A Variational Edge Partition Model for Supervised Graph Representation Learning | Feb 7, 2022 | ClassificationGraph Representation Learning | CodeCode Available | 0 | 5 |
| A Contrastive Divergence for Combining Variational Inference and MCMC | May 10, 2019 | Stochastic OptimizationVariational 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 |
| Amortized Variational Inference: When and Why? | Jul 20, 2023 | Bayesian InferenceGaussian Processes | CodeCode Available | 0 | 5 |
| Distributional Bayesian optimisation for variational inference on black-box simulators | Oct 16, 2019 | Bayesian OptimisationVariational Inference | CodeCode Available | 0 | 5 |
| Dropout Inference in Bayesian Neural Networks with Alpha-divergences | Mar 8, 2017 | Variational Inference | CodeCode Available | 0 | 5 |
| Discretely Relaxing Continuous Variables for tractable Variational Inference | Dec 1, 2018 | Variational Inference | CodeCode Available | 0 | 5 |
