| Interval Neural Networks as Instability Detectors for Image Reconstructions | Mar 27, 2020 | Deep LearningImage Reconstruction | CodeCode Available | 0 |
| Interval Neural Networks: Uncertainty Scores | Mar 25, 2020 | Image ReconstructionUncertainty Quantification | CodeCode Available | 0 |
| On Calibration of Mixup Training for Deep Neural Networks | Mar 22, 2020 | Data AugmentationUncertainty Quantification | CodeCode Available | 0 |
| Nearest Neighbor Dirichlet Mixtures | Mar 17, 2020 | Density EstimationUncertainty Quantification | CodeCode Available | 0 |
| Uncertainty Quantification for Demand Prediction in Contextual Dynamic Pricing | Mar 16, 2020 | Assortment OptimizationManagement | —Unverified | 0 |
| B-PINNs: Bayesian Physics-Informed Neural Networks for Forward and Inverse PDE Problems with Noisy Data | Mar 13, 2020 | Uncertainty QuantificationVariational Inference | —Unverified | 0 |
| Scalable Uncertainty for Computer Vision with Functional Variational Inference | Mar 6, 2020 | Depth EstimationGaussian Processes | —Unverified | 0 |
| Uncertainty Estimation Using a Single Deep Deterministic Neural Network | Mar 4, 2020 | Out-of-Distribution DetectionUncertainty Quantification | CodeCode Available | 1 |
| Uncertainty Quantification for Deep Context-Aware Mobile Activity Recognition and Unknown Context Discovery | Mar 3, 2020 | Activity RecognitionClustering | —Unverified | 0 |
| Uncertainty Quantification for Sparse Deep Learning | Feb 26, 2020 | Deep LearningUncertainty Quantification | —Unverified | 0 |
| 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 |
| 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 |
