| Deep Echo State Networks with Uncertainty Quantification for Spatio-Temporal Forecasting | Jun 28, 2018 | Spatio-Temporal ForecastingUncertainty Quantification | —Unverified | 0 | 0 |
| Deep Ensemble as a Gaussian Process Approximate Posterior | Apr 30, 2022 | Bayesian InferenceUncertainty Quantification | —Unverified | 0 | 0 |
| Deep-Ensemble-Based Uncertainty Quantification in Spatiotemporal Graph Neural Networks for Traffic Forecasting | Apr 4, 2022 | Bayesian OptimizationHyperparameter Optimization | —Unverified | 0 | 0 |
| Deep Ensembles from a Bayesian Perspective | May 27, 2021 | Uncertainty Quantification | —Unverified | 0 | 0 |
| Deep Ensembles to Improve Uncertainty Quantification of Statistical Downscaling Models under Climate Change Conditions | Apr 27, 2023 | Uncertainty Quantification | —Unverified | 0 | 0 |
| Deep Evidential Learning for Bayesian Quantile Regression | Aug 21, 2023 | Disentanglementquantile regression | —Unverified | 0 | 0 |
| Deep Evidential Learning for Radiotherapy Dose Prediction | Apr 26, 2024 | PredictionUncertainty Quantification | —Unverified | 0 | 0 |
| DeepGLEAM: A hybrid mechanistic and deep learning model for COVID-19 forecasting | Feb 12, 2021 | Deep LearningUncertainty Quantification | —Unverified | 0 | 0 |
| Deep interpretable ensembles | May 25, 2022 | Uncertainty Quantification | —Unverified | 0 | 0 |
| Deep Latent Force Models: ODE-based Process Convolutions for Bayesian Deep Learning | Nov 24, 2023 | Time SeriesUncertainty Quantification | —Unverified | 0 | 0 |
