| Adversarial Uncertainty Quantification in Physics-Informed Neural Networks | Nov 9, 2018 | Uncertainty Quantification | CodeCode Available | 0 |
| Uncertainty in Neural Networks: Approximately Bayesian Ensembling | Oct 12, 2018 | Bayesian InferenceGeneral Classification | CodeCode Available | 0 |
| Quantifying total uncertainty in physics-informed neural networks for solving forward and inverse stochastic problems | Sep 21, 2018 | Active LearningUncertainty Quantification | —Unverified | 0 |
| Data-driven polynomial chaos expansion for machine learning regression | Aug 9, 2018 | BIG-bench Machine Learningregression | —Unverified | 0 |
| Uncertainty Quantification in CNN-Based Surface Prediction Using Shape Priors | Jul 30, 2018 | Medical Image AnalysisProbabilistic Deep Learning | —Unverified | 0 |
| Estimating Failure in Brittle Materials using Graph Theory | Jul 30, 2018 | Uncertainty Quantification | —Unverified | 0 |
| Weak in the NEES?: Auto-tuning Kalman Filters with Bayesian Optimization | Jul 23, 2018 | Bayesian OptimizationSimultaneous Localization and Mapping | —Unverified | 0 |
| Algorithmic Framework for Model-based Deep Reinforcement Learning with Theoretical Guarantees | Jul 10, 2018 | continuous-controlContinuous Control | CodeCode Available | 0 |
| Quantifying model form uncertainty in Reynolds-averaged turbulence models with Bayesian deep neural networks | Jul 8, 2018 | FormUncertainty Quantification | CodeCode Available | 0 |
| Deep convolutional encoder-decoder networks for uncertainty quantification of dynamic multiphase flow in heterogeneous media | Jul 2, 2018 | Computational EfficiencyDecoder | CodeCode Available | 0 |
| Fully Nonparametric Bayesian Additive Regression Trees | Jun 29, 2018 | regressionUncertainty Quantification | —Unverified | 0 |
| Deep Echo State Networks with Uncertainty Quantification for Spatio-Temporal Forecasting | Jun 28, 2018 | Spatio-Temporal ForecastingUncertainty Quantification | —Unverified | 0 |
| Neural-net-induced Gaussian process regression for function approximation and PDE solution | Jun 22, 2018 | Gaussian Processesregression | —Unverified | 0 |
| A data-driven model order reduction approach for Stokes flow through random porous media | Jun 21, 2018 | Uncertainty Quantification | —Unverified | 0 |
| Evidential Deep Learning to Quantify Classification Uncertainty | Jun 5, 2018 | Deep LearningGeneral Classification | CodeCode Available | 1 |
| Bayesian approach to model-based extrapolation of nuclear observables | Jun 1, 2018 | Gaussian ProcessesUncertainty Quantification | —Unverified | 0 |
| Dirichlet-based Gaussian Processes for Large-scale Calibrated Classification | May 28, 2018 | ClassificationGaussian Processes | CodeCode Available | 0 |
| Probabilistic Riemannian submanifold learning with wrapped Gaussian process latent variable models | May 23, 2018 | Uncertainty Quantification | —Unverified | 0 |
| Deep Directional Statistics: Pose Estimation with Uncertainty Quantification | May 9, 2018 | Deep LearningPose Estimation | CodeCode Available | 0 |
| Bayeslands: A Bayesian inference approach for parameter uncertainty quantification in Badlands | May 2, 2018 | Bayesian InferenceUncertainty Quantification | CodeCode Available | 0 |
| Uncertainty quantification using Bayesian neural networks in classification: Application to ischemic stroke lesion segmentation | Apr 10, 2018 | General ClassificationIschemic Stroke Lesion Segmentation | —Unverified | 0 |
| Pseudo-marginal Bayesian inference for supervised Gaussian process latent variable models | Mar 28, 2018 | Bayesian InferenceUncertainty Quantification | —Unverified | 0 |
| Dimension-Robust MCMC in Bayesian Inverse Problems | Mar 9, 2018 | Active LearningEfficient Exploration | —Unverified | 0 |
| High-Quality Prediction Intervals for Deep Learning: A Distribution-Free, Ensembled Approach | Feb 20, 2018 | FormPrediction Intervals | CodeCode Available | 0 |
| Constraining the Dynamics of Deep Probabilistic Models | Feb 15, 2018 | Uncertainty QuantificationVariational Inference | —Unverified | 0 |
