Variational refinement for importance sampling using the forward Kullback-Leibler divergence. | 0 | 0.34 | 2021 |
Combining Ensembles and Data Augmentation Can Harm Your Calibration. | 0 | 0.34 | 2021 |
Benchmarking Bayesian Deep Learning on Diabetic Retinopathy Detection Tasks. | 0 | 0.34 | 2021 |
Efficient and Scalable Bayesian Neural Nets with Rank-1 Factors | 0 | 0.34 | 2020 |
Analyzing the role of model uncertainty for electronic health records. | 3 | 0.44 | 2020 |
Reconciling meta-learning and continual learning with online mixtures of tasks | 1 | 0.35 | 2019 |
AdaNet: A Scalable and Flexible Framework for Automatically Learning Ensembles | 0 | 0.34 | 2019 |
Measuring Calibration in Deep Learning. | 1 | 0.35 | 2019 |
Online gradient-based mixtures for transfer modulation in meta-learning. | 1 | 0.36 | 2018 |