| Maximum likelihood estimation and uncertainty quantification for Gaussian process approximation of deterministic functions | Jan 29, 2020 | regressionUncertainty Quantification | —Unverified | 0 |
| Certified and fast computations with shallow covariance kernels | Jan 24, 2020 | Uncertainty Quantification | —Unverified | 0 |
| On Last-Layer Algorithms for Classification: Decoupling Representation from Uncertainty Estimation | Jan 22, 2020 | General ClassificationRepresentation Learning | CodeCode Available | 0 |
| Finding Optimal Points for Expensive Functions Using Adaptive RBF-Based Surrogate Model Via Uncertainty Quantification | Jan 19, 2020 | global-optimizationUncertainty Quantification | —Unverified | 0 |
| Building high accuracy emulators for scientific simulations with deep neural architecture search | Jan 17, 2020 | Neural Architecture Searchscientific discovery | —Unverified | 0 |
| Training Normalizing Flows with the Information Bottleneck for Competitive Generative Classification | Jan 17, 2020 | General ClassificationOut-of-Distribution Detection | CodeCode Available | 1 |
| Tackling small eigen-gaps: Fine-grained eigenvector estimation and inference under heteroscedastic noise | Jan 14, 2020 | Uncertainty Quantification | —Unverified | 0 |
| A deep-learning based Bayesian approach to seismic imaging and uncertainty quantification | Jan 13, 2020 | Seismic ImagingUncertainty Quantification | CodeCode Available | 0 |
| Considering discrepancy when calibrating a mechanistic electrophysiology model | Jan 13, 2020 | Gaussian ProcessesUncertainty Quantification | CodeCode Available | 0 |
| Machine Learning for Clouds and Climate | Jan 1, 2020 | BIG-bench Machine LearningCloud Detection | —Unverified | 0 |
