| Generalized Variational Continual Learning | Nov 24, 2020 | Continual LearningVariational Inference | —Unverified | 0 |
| Parametric Bootstrap Ensembles as Variational Inference | Nov 23, 2020 | Bayesian InferenceVariational Inference | —Unverified | 0 |
| Generative Video Compression as Hierarchical Variational Inference | Nov 23, 2020 | Density EstimationVariational Inference | —Unverified | 0 |
| Gaussian Process Latent Variable Flows for Massively Missing Data | Nov 23, 2020 | Dimensionality ReductionGaussian Processes | —Unverified | 0 |
| Gaussian Density Parametrization Flow: Particle and Stochastic Approaches | Nov 23, 2020 | Bayesian InferenceVariational Inference | —Unverified | 0 |
| Scalable Hybrid Hidden Markov Model with Gaussian Process Emission for Sequential Time-series Observations | Nov 23, 2020 | Time SeriesTime Series Analysis | —Unverified | 0 |
| Neural Linear Models with Functional Gaussian Process Priors | Nov 23, 2020 | Gaussian Processesregression | —Unverified | 0 |
| The Gaussian Process Latent Autoregressive Model | Nov 23, 2020 | DenoisingGaussian Processes | —Unverified | 0 |
| Gradient Regularisation as Approximate Variational Inference | Nov 23, 2020 | Variational Inference | —Unverified | 0 |
| Rethinking Function-Space Variational Inference in Bayesian Neural Networks | Nov 23, 2020 | Variational Inference | —Unverified | 0 |
