| Variational Memory Addressing in Generative Models | Sep 21, 2017 | Few-Shot LearningRepresentation Learning | CodeCode Available | 0 |
| Improving Explorability in Variational Inference with Annealed Variational Objectives | Sep 6, 2018 | Variational Inference | CodeCode Available | 0 |
| Improving Fair Predictions Using Variational Inference In Causal Models | Aug 25, 2020 | BIG-bench Machine LearningFairness | CodeCode Available | 0 |
| Black-box Coreset Variational Inference | Nov 4, 2022 | Bayesian InferenceData Summarization | CodeCode Available | 0 |
| Improving Hyperparameter Learning under Approximate Inference in Gaussian Process Models | Jun 7, 2023 | Hyperparameter OptimizationVariational Inference | CodeCode Available | 0 |
| Learning Deep Generative Models with Annealed Importance Sampling | Jun 12, 2019 | Variational Inference | CodeCode Available | 0 |
| Debiasing Evidence Approximations: On Importance-weighted Autoencoders and Jackknife Variational Inference | Jan 1, 2018 | Computational EfficiencyVariational Inference | CodeCode Available | 0 |
| Improving model calibration with accuracy versus uncertainty optimization | Dec 14, 2020 | image-classificationImage Classification | CodeCode Available | 0 |
| Uncertainty Quantification using Variational Inference for Biomedical Image Segmentation | Aug 12, 2020 | Decoderimage-classification | CodeCode Available | 0 |
| Variational Gibbs Inference for Statistical Model Estimation from Incomplete Data | Nov 25, 2021 | BIG-bench Machine LearningNormalising Flows | CodeCode Available | 0 |
