| Uncertainty Quantification in CNN-Based Surface Prediction Using Shape Priors | Jul 30, 2018 | Medical Image AnalysisProbabilistic Deep Learning | —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 |
| Bayesian approach to model-based extrapolation of nuclear observables | Jun 1, 2018 | Gaussian ProcessesUncertainty Quantification | —Unverified | 0 |
