| AutoPQ: Automating Quantile estimation from Point forecasts in the context of sustainability | Nov 30, 2024 | Uncertainty Quantification | —Unverified | 0 | 0 |
| Auto-weighted Bayesian Physics-Informed Neural Networks and robust estimations for multitask inverse problems in pore-scale imaging of dissolution | Aug 24, 2023 | Bayesian InferenceUncertainty Quantification | —Unverified | 0 | 0 |
| A variational Bayesian spatial interaction model for estimating revenue and demand at business facilities | Aug 5, 2021 | Decision MakingUncertainty Quantification | —Unverified | 0 | 0 |
| A Variational Inference Approach to Inverse Problems with Gamma Hyperpriors | Nov 26, 2021 | Model SelectionTime Series | —Unverified | 0 | 0 |
| A view on model misspecification in uncertainty quantification | Oct 30, 2022 | modelUncertainty Quantification | —Unverified | 0 | 0 |
| Information-Geometric Barycenters for Bayesian Federated Learning | Dec 16, 2024 | Bayesian InferenceDistributed Optimization | —Unverified | 0 | 0 |
| BARK: A Fully Bayesian Tree Kernel for Black-box Optimization | Mar 7, 2025 | Bayesian OptimizationGaussian Processes | —Unverified | 0 | 0 |
| BARNN: A Bayesian Autoregressive and Recurrent Neural Network | Jan 30, 2025 | Bayesian InferenceUncertainty Quantification | —Unverified | 0 | 0 |
| Barrier Certificates for Unknown Systems with Latent States and Polynomial Dynamics using Bayesian Inference | Apr 2, 2025 | Bayesian InferenceUncertainty Quantification | —Unverified | 0 | 0 |
| Batch-Ensemble Stochastic Neural Networks for Out-of-Distribution Detection | Jun 26, 2022 | BIG-bench Machine LearningOut-of-Distribution Detection | —Unverified | 0 | 0 |
