| Approximate Message Passing for Bayesian Neural Networks | Jan 26, 2025 | Uncertainty QuantificationVariational Inference | CodeCode Available | 0 | 5 |
| Evidential Deep Learning for Uncertainty Quantification and Out-of-Distribution Detection in Jet Identification using Deep Neural Networks | Jan 10, 2025 | Anomaly DetectionBenchmarking | CodeCode Available | 0 | 5 |
| E-Values Expand the Scope of Conformal Prediction | Mar 17, 2025 | Conformal PredictionPrediction | CodeCode Available | 0 | 5 |
| Evidential Deep Learning for Probabilistic Modelling of Extreme Storm Events | Dec 18, 2024 | Deep LearningUncertainty Quantification | CodeCode Available | 0 | 5 |
| Exploring the Limits of Epistemic Uncertainty Quantification in Low-Shot Settings | Nov 18, 2021 | Out-of-Distribution DetectionUncertainty Quantification | CodeCode Available | 0 | 5 |
| Fully Bayesian inference for latent variable Gaussian process models | Nov 4, 2022 | Bayesian InferenceGaussian Processes | CodeCode Available | 0 | 5 |
| Improving Uncertainty Quantification of Variance Networks by Tree-Structured Learning | Dec 24, 2022 | Uncertainty Quantification | CodeCode Available | 0 | 5 |
| Equivariant Bootstrapping for Uncertainty Quantification in Imaging Inverse Problems | Oct 18, 2023 | Image ReconstructionUncertainty Quantification | CodeCode Available | 0 | 5 |
| Equivariant Neural Simulators for Stochastic Spatiotemporal Dynamics | May 23, 2023 | Uncertainty Quantification | CodeCode Available | 0 | 5 |
| Estimating prevalence with precision and accuracy | Jul 8, 2025 | Uncertainty Quantification | CodeCode Available | 0 | 5 |
