| Conformal Inference of Counterfactuals and Individual Treatment Effects | Jun 11, 2020 | Decision MakingUncertainty Quantification | CodeCode Available | 1 |
| Uncertainty quantification in medical image segmentation with normalizing flows | Jun 4, 2020 | DiversityImage Segmentation | CodeCode Available | 1 |
| Unsupervised Quality Estimation for Neural Machine Translation | May 21, 2020 | Machine TranslationTranslation | CodeCode Available | 1 |
| Uncertainty Quantification Using Neural Networks for Molecular Property Prediction | May 20, 2020 | Drug DiscoveryExperimental Design | CodeCode Available | 1 |
| Deeply Uncertain: Comparing Methods of Uncertainty Quantification in Deep Learning Algorithms | Apr 22, 2020 | Uncertainty Quantification | CodeCode Available | 1 |
| Parameterizing uncertainty by deep invertible networks, an application to reservoir characterization | Apr 16, 2020 | Uncertainty Quantification | CodeCode Available | 1 |
| From Fourier to Koopman: Spectral Methods for Long-term Time Series Prediction | Apr 1, 2020 | Time SeriesTime Series Analysis | CodeCode Available | 1 |
| Uncertainty quantification in imaging and automatic horizon tracking: a Bayesian deep-prior based approach | Apr 1, 2020 | Seismic ImagingSensitivity | CodeCode Available | 1 |
| Uncertainty Estimation Using a Single Deep Deterministic Neural Network | Mar 4, 2020 | Out-of-Distribution DetectionUncertainty Quantification | CodeCode Available | 1 |
| BatchEnsemble: An Alternative Approach to Efficient Ensemble and Lifelong Learning | Feb 17, 2020 | de-enLifelong learning | CodeCode Available | 1 |
| PDE-NetGen 1.0: from symbolic PDE representations of physical processes to trainable neural network representations | Feb 3, 2020 | Uncertainty Quantification | CodeCode Available | 1 |
| Training Normalizing Flows with the Information Bottleneck for Competitive Generative Classification | Jan 17, 2020 | General ClassificationOut-of-Distribution Detection | CodeCode Available | 1 |
| Bayesian Meta-Learning for the Few-Shot Setting via Deep Kernels | Oct 11, 2019 | Bayesian InferenceDomain Adaptation | CodeCode Available | 1 |
| Stochastic Optimal Control as Approximate Input Inference | Oct 7, 2019 | Uncertainty Quantification | CodeCode Available | 1 |
| Deep Evidential Regression | Oct 7, 2019 | regressionUncertainty Quantification | CodeCode Available | 1 |
| Building Calibrated Deep Models via Uncertainty Matching with Auxiliary Interval Predictors | Sep 9, 2019 | Object LocalizationPrediction | CodeCode Available | 1 |
| Deep learning observables in computational fluid dynamics | Mar 7, 2019 | Deep LearningEfficient Neural Network | CodeCode Available | 1 |
| Deep active subspaces - a scalable method for high-dimensional uncertainty propagation | Feb 27, 2019 | Dimensionality ReductionUncertainty Quantification | CodeCode Available | 1 |
| A Simple Baseline for Bayesian Uncertainty in Deep Learning | Feb 7, 2019 | Bayesian InferenceDeep Learning | CodeCode Available | 1 |
| Evidential Deep Learning to Quantify Classification Uncertainty | Jun 5, 2018 | Deep LearningGeneral Classification | CodeCode Available | 1 |
| Deep UQ: Learning deep neural network surrogate models for high dimensional uncertainty quantification | Feb 2, 2018 | Uncertainty Quantification | CodeCode Available | 1 |
| Finite-dimensional Gaussian approximation with linear inequality constraints | Oct 20, 2017 | parameter estimationUncertainty Quantification | CodeCode Available | 1 |
| Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles | Dec 5, 2016 | Image Classificationregression | CodeCode Available | 1 |
| Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning | Jun 6, 2015 | Bayesian InferenceDeep Reinforcement Learning | CodeCode Available | 1 |
| Distributional Reinforcement Learning on Path-dependent Options | Jul 16, 2025 | Distributional Reinforcement Learningreinforcement-learning | —Unverified | 0 |
