| Uncertainty quantification with approximate variational learning for wearable photoplethysmography prediction tasks | May 16, 2025 | Photoplethysmography (PPG)Uncertainty Quantification | —Unverified | 0 | 0 |
| Exchangeable Sequence Models Quantify Uncertainty Over Latent Concepts | Aug 6, 2024 | Bayesian InferenceData Augmentation | —Unverified | 0 | 0 |
| Uncertainty Quantification with Statistical Guarantees in End-to-End Autonomous Driving Control | Sep 21, 2019 | Autonomous DrivingBayesian Inference | —Unverified | 0 | 0 |
| Efficient Conformal Prediction under Data Heterogeneity | Dec 25, 2023 | Conformal PredictionFederated Learning | —Unverified | 0 | 0 |
| Beyond mirkwood: Enhancing SED Modeling with Conformal Predictions | Dec 21, 2023 | Conformal Predictionquantile regression | —Unverified | 0 | 0 |
| Efficient Bayesian Physics Informed Neural Networks for Inverse Problems via Ensemble Kalman Inversion | Mar 13, 2023 | Physics-informed machine learningUncertainty Quantification | —Unverified | 0 | 0 |
| Beyond Glass-Box Features: Uncertainty Quantification Enhanced Quality Estimation for Neural Machine Translation | Sep 15, 2021 | Feature EngineeringLanguage Modeling | —Unverified | 0 | 0 |
| Application of Deep Learning-based Interpolation Methods to Nearshore Bathymetry | Nov 19, 2020 | Deep LearningGenerative Adversarial Network | —Unverified | 0 | 0 |
| Efficient Bayesian Computation Using Plug-and-Play Priors for Poisson Inverse Problems | Mar 20, 2025 | AstronomyBayesian Inference | —Unverified | 0 | 0 |
| Efficient and Scalable Bayesian Neural Nets with Rank-1 Factors | May 14, 2020 | Uncertainty Quantification | —Unverified | 0 | 0 |
