| Composing Normalizing Flows for Inverse Problems | Feb 26, 2020 | Compressive SensingUncertainty Quantification | —Unverified | 0 |
| A Comparative Study of Machine Learning Models for Predicting the State of Reactive Mixing | Feb 24, 2020 | BIG-bench Machine LearningEnsemble Learning | CodeCode Available | 0 |
| BatchEnsemble: An Alternative Approach to Efficient Ensemble and Lifelong Learning | Feb 17, 2020 | de-enLifelong learning | CodeCode Available | 1 |
| Learnable Bernoulli Dropout for Bayesian Deep Learning | Feb 12, 2020 | Collaborative FilteringDeep Learning | —Unverified | 0 |
| Statistical aspects of nuclear mass models | Feb 11, 2020 | DiagnosticUncertainty Quantification | —Unverified | 0 |
| On transfer learning of neural networks using bi-fidelity data for uncertainty propagation | Feb 11, 2020 | Transfer LearningUncertainty Quantification | —Unverified | 0 |
| How Good is the Bayes Posterior in Deep Neural Networks Really? | Feb 6, 2020 | Bayesian InferenceDeep Learning | —Unverified | 0 |
| Uncertainty Quantification for Bayesian Optimization | Feb 4, 2020 | Bayesian Optimizationglobal-optimization | —Unverified | 0 |
| PDE-NetGen 1.0: from symbolic PDE representations of physical processes to trainable neural network representations | Feb 3, 2020 | Uncertainty Quantification | CodeCode Available | 1 |
| Towards a Kernel based Uncertainty Decomposition Framework for Data and Models | Jan 30, 2020 | Time Series AnalysisUncertainty Quantification | —Unverified | 0 |
