| BayesAdapter: Being Bayesian, Inexpensively and Robustly, via Bayesian Fine-tuning | Sep 28, 2020 | Uncertainty QuantificationVariational Inference | —Unverified | 0 |
| Dynamic graph and polynomial chaos based models for contact tracing data analysis and optimal testing prescription | Sep 10, 2020 | Uncertainty Quantification | —Unverified | 0 |
| Automatic selection of basis-adaptive sparse polynomial chaos expansions for engineering applications | Sep 10, 2020 | Compressive SensingExperimental Design | —Unverified | 0 |
| Improved Trainable Calibration Method for Neural Networks on Medical Imaging Classification | Sep 9, 2020 | ClassificationDecision Making | —Unverified | 0 |
| Mutual Information for Explainable Deep Learning of Multiscale Systems | Sep 7, 2020 | Deep LearningUncertainty Quantification | —Unverified | 0 |
| Uncertainty quantification for Markov Random Fields | Aug 31, 2020 | Uncertainty Quantification | —Unverified | 0 |
| SDE-Net: Equipping Deep Neural Networks with Uncertainty Estimates | Aug 24, 2020 | Uncertainty Quantification | CodeCode Available | 1 |
| Doubly Stochastic Variational Inference for Neural Processes with Hierarchical Latent Variables | Aug 21, 2020 | Computational Efficiencyregression | —Unverified | 0 |
| Uncertainty Estimation in Medical Image Denoising with Bayesian Deep Image Prior | Aug 20, 2020 | DenoisingImage Denoising | CodeCode Available | 1 |
| Bayesian neural networks and dimensionality reduction | Aug 18, 2020 | Bayesian InferenceDimensionality Reduction | —Unverified | 0 |
