| 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 |
| HiGrad: Uncertainty Quantification for Online Learning and Stochastic Approximation | Feb 13, 2018 | Uncertainty Quantification | —Unverified | 0 |
