| JaxSGMC: Modular stochastic gradient MCMC in JAX | May 16, 2025 | Deep LearningStochastic Optimization | CodeCode Available | 1 | 5 |
| Error-quantified Conformal Inference for Time Series | Feb 2, 2025 | PredictionTime Series | CodeCode Available | 1 | 5 |
| Bayesian graph convolutional neural networks via tempered MCMC | Apr 17, 2021 | Bayesian InferenceDeep Learning | CodeCode Available | 1 | 5 |
| Bayesian Few-Shot Classification with One-vs-Each Pólya-Gamma Augmented Gaussian Processes | Jul 20, 2020 | ClassificationGaussian Processes | CodeCode Available | 1 | 5 |
| Adaptive Conformal Predictions for Time Series | Feb 15, 2022 | Conformal PredictionDecision Making | CodeCode Available | 1 | 5 |
| Evidential Uncertainty Quantification: A Variance-Based Perspective | Nov 19, 2023 | Active LearningClassification | CodeCode Available | 1 | 5 |
| AdaPTS: Adapting Univariate Foundation Models to Probabilistic Multivariate Time Series Forecasting | Feb 14, 2025 | Multivariate Time Series ForecastingRepresentation Learning | CodeCode Available | 1 | 5 |
| Training Normalizing Flows with the Information Bottleneck for Competitive Generative Classification | Jan 17, 2020 | General ClassificationOut-of-Distribution Detection | CodeCode Available | 1 | 5 |
| Deep learning observables in computational fluid dynamics | Mar 7, 2019 | Deep LearningEfficient Neural Network | CodeCode Available | 1 | 5 |
| Bayesian Physics Informed Neural Networks for Data Assimilation and Spatio-Temporal Modelling of Wildfires | Dec 2, 2022 | Uncertainty Quantification | CodeCode Available | 1 | 5 |
| Likelihood-Free Parameter Estimation with Neural Bayes Estimators | Aug 27, 2022 | parameter estimationUncertainty Quantification | CodeCode Available | 1 | 5 |
| FastSAM-3DSlicer: A 3D-Slicer Extension for 3D Volumetric Segment Anything Model with Uncertainty Quantification | Jul 17, 2024 | CPUDomain Adaptation | CodeCode Available | 1 | 5 |
| Deep UQ: Learning deep neural network surrogate models for high dimensional uncertainty quantification | Feb 2, 2018 | Uncertainty Quantification | CodeCode Available | 1 | 5 |
| Finite-dimensional Gaussian approximation with linear inequality constraints | Oct 20, 2017 | parameter estimationUncertainty Quantification | CodeCode Available | 1 | 5 |
| BayOTIDE: Bayesian Online Multivariate Time series Imputation with functional decomposition | Aug 28, 2023 | Computational EfficiencyGaussian Processes | CodeCode Available | 1 | 5 |
| AMICI: High-Performance Sensitivity Analysis for Large Ordinary Differential Equation Models | Dec 16, 2020 | parameter estimationSensitivity | CodeCode Available | 1 | 5 |
| Deep Generative Data Assimilation in Multimodal Setting | Apr 10, 2024 | Image GenerationUncertainty Quantification | CodeCode Available | 1 | 5 |
| Arctique: An artificial histopathological dataset unifying realism and controllability for uncertainty quantification | Nov 11, 2024 | BenchmarkingImage Segmentation | CodeCode Available | 1 | 5 |
| A Simple Baseline for Bayesian Uncertainty in Deep Learning | Feb 7, 2019 | Bayesian InferenceDeep Learning | CodeCode Available | 1 | 5 |
| AutoIP: A United Framework to Integrate Physics into Gaussian Processes | Feb 24, 2022 | Gaussian ProcessesUncertainty Quantification | CodeCode Available | 1 | 5 |
| Disentangling Uncertainty in Machine Translation Evaluation | Apr 13, 2022 | Machine TranslationPrediction | CodeCode Available | 1 | 5 |
| Generating with Confidence: Uncertainty Quantification for Black-box Large Language Models | May 30, 2023 | ManagementQuestion Answering | CodeCode Available | 1 | 5 |
| Bayesian Meta-Learning for the Few-Shot Setting via Deep Kernels | Oct 11, 2019 | Bayesian InferenceDomain Adaptation | CodeCode Available | 1 | 5 |
| Gradient-free variational learning with conditional mixture networks | Aug 29, 2024 | Computational EfficiencyMixture-of-Experts | CodeCode Available | 1 | 5 |
| Deep Deterministic Uncertainty: A Simple Baseline | Feb 23, 2021 | Active LearningUncertainty Quantification | CodeCode Available | 1 | 5 |
