| The Shrinkage-Delinkage Trade-off: An Analysis of Factorized Gaussian Approximations for Variational Inference | Feb 17, 2023 | Variational Inference | CodeCode Available | 0 |
| Piecewise Deterministic Markov Processes for Bayesian Neural Networks | Feb 17, 2023 | Variational Inference | CodeCode Available | 0 |
| GFlowNet-EM for learning compositional latent variable models | Feb 13, 2023 | Variational Inference | CodeCode Available | 1 |
| Variational Bayesian Neural Networks via Resolution of Singularities | Feb 13, 2023 | Learning TheoryVariational Inference | CodeCode Available | 0 |
| Differentially Private Normalizing Flows for Density Estimation, Data Synthesis, and Variational Inference with Application to Electronic Health Records | Feb 11, 2023 | Density EstimationPrivacy Preserving | CodeCode Available | 0 |
| Gaussian Process-Gated Hierarchical Mixtures of Experts | Feb 9, 2023 | Gaussian ProcessesVariational Inference | CodeCode Available | 0 |
| A Benchmark on Uncertainty Quantification for Deep Learning Prognostics | Feb 9, 2023 | Active LearningDecision Making | CodeCode Available | 1 |
| Federated Learning as Variational Inference: A Scalable Expectation Propagation Approach | Feb 8, 2023 | Distributed OptimizationFederated Learning | CodeCode Available | 1 |
| Federated Variational Inference Methods for Structured Latent Variable Models | Feb 7, 2023 | Federated LearningTopic Models | —Unverified | 0 |
| Prior Density Learning in Variational Bayesian Phylogenetic Parameters Inference | Feb 6, 2023 | Variational Inference | CodeCode Available | 0 |
