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| The Variational Predictive Natural Gradient | Mar 7, 2019 | General ClassificationVariational Inference | CodeCode Available | 0 |
| Variational Inference with Normalizing Flows | May 21, 2015 | Variational Inference | CodeCode Available | 0 |
| Doubly Reparameterized Gradient Estimators for Monte Carlo Objectives | Oct 9, 2018 | Variational Inference | CodeCode Available | 0 |
| Conditional Deep Gaussian Processes: multi-fidelity kernel learning | Feb 7, 2020 | Few-Shot LearningGaussian Processes | CodeCode Available | 0 |
| Thompson Sampling for High-Dimensional Sparse Linear Contextual Bandits | Nov 11, 2022 | Multi-Armed BanditsThompson Sampling | CodeCode Available | 0 |
| Doubly Stochastic Variational Inference for Deep Gaussian Processes | May 24, 2017 | Gaussian ProcessesGeneral Classification | CodeCode Available | 0 |
| Variational inference for Monte Carlo objectives | Feb 22, 2016 | Variational Inference | CodeCode Available | 0 |
| Thompson Sampling via Local Uncertainty | Oct 30, 2019 | Decision MakingMulti-Armed Bandits | CodeCode Available | 0 |
| A Hierarchical Bayesian Model for Deep Few-Shot Meta Learning | Jun 16, 2023 | Bayesian InferenceMeta-Learning | CodeCode Available | 0 |
