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| Bayesian Physics-Informed Extreme Learning Machine for Forward and Inverse PDE Problems with Noisy Data | May 14, 2022 | Uncertainty Quantification | —Unverified | 0 |
| A hybrid data driven-physics constrained Gaussian process regression framework with deep kernel for uncertainty quantification | May 13, 2022 | GPRregression | —Unverified | 0 |
| Generalized Variational Inference in Function Spaces: Gaussian Measures meet Bayesian Deep Learning | May 12, 2022 | Gaussian ProcessesUncertainty Quantification | CodeCode Available | 0 |
| Bayesian Physics-Informed Neural Networks for real-world nonlinear dynamical systems | May 12, 2022 | Bayesian InferenceModel Selection | —Unverified | 0 |
| Extensible Machine Learning for Encrypted Network Traffic Application Labeling via Uncertainty Quantification | May 11, 2022 | BIG-bench Machine LearningUncertainty Quantification | —Unverified | 0 |
| De-biasing "bias" measurement | May 11, 2022 | Decision MakingFairness | CodeCode Available | 0 |
| Recurrent Encoder-Decoder Networks for Vessel Trajectory Prediction with Uncertainty Estimation | May 11, 2022 | DecoderDeep Learning | —Unverified | 0 |
| Large Scale Probabilistic Simulation of Renewables Production | May 10, 2022 | ClusteringUncertainty Quantification | —Unverified | 0 |
| A Unified Bayesian Framework for Pricing Catastrophe Bond Derivatives | May 9, 2022 | ClusteringUncertainty Quantification | —Unverified | 0 |
