| Modified Frank Wolfe in Probability Space | Dec 1, 2021 | Variational Inference | —Unverified | 0 |
| Functional Variational Inference based on Stochastic Process Generators | Dec 1, 2021 | Bayesian InferenceVariational Inference | —Unverified | 0 |
| Scalable Bayesian GPFA with automatic relevance determination and discrete noise models | Dec 1, 2021 | Variational Inference | —Unverified | 0 |
| Learning to Learn Dense Gaussian Processes for Few-Shot Learning | Dec 1, 2021 | Few-Shot LearningGaussian Processes | —Unverified | 0 |
| Variational Continual Bayesian Meta-Learning | Dec 1, 2021 | Meta-LearningTransfer Learning | —Unverified | 0 |
| A Gaussian Process-Bayesian Bernoulli Mixture Model for Multi-Label Active Learning | Dec 1, 2021 | Active LearningInductive Bias | —Unverified | 0 |
| Probabilistic Tensor Decomposition of Neural Population Spiking Activity | Dec 1, 2021 | AnatomyTensor Decomposition | CodeCode Available | 0 |
| A Variational Inference Approach to Inverse Problems with Gamma Hyperpriors | Nov 26, 2021 | Model SelectionTime Series | —Unverified | 0 |
| Differentially private stochastic expectation propagation (DP-SEP) | Nov 25, 2021 | Variational Inference | —Unverified | 0 |
| Variational Gibbs Inference for Statistical Model Estimation from Incomplete Data | Nov 25, 2021 | BIG-bench Machine LearningNormalising Flows | CodeCode Available | 0 |
