| Constraining cosmological parameters from N-body simulations with Variational Bayesian Neural Networks | Jan 9, 2023 | Uncertainty Quantification | —Unverified | 0 |
| Deep Injective Prior for Inverse Scattering | Jan 8, 2023 | Uncertainty Quantification | CodeCode Available | 0 |
| L-HYDRA: Multi-Head Physics-Informed Neural Networks | Jan 5, 2023 | Few-Shot LearningMeta-Learning | CodeCode Available | 0 |
| Deep Deterministic Uncertainty: A New Simple Baseline | Jan 1, 2023 | Active LearningSemantic Segmentation | —Unverified | 0 |
| Non-intrusive surrogate modelling using sparse random features with applications in crashworthiness analysis | Dec 30, 2022 | Dimensionality ReductionSupervised dimensionality reduction | —Unverified | 0 |
| Posterior sampling with CNN-based, Plug-and-Play regularization with applications to Post-Stack Seismic Inversion | Dec 30, 2022 | Decision MakingSeismic Inversion | —Unverified | 0 |
| A Learning-Based Optimal Uncertainty Quantification Method and Its Application to Ballistic Impact Problems | Dec 28, 2022 | Uncertainty Quantification | —Unverified | 0 |
| Improving Uncertainty Quantification of Variance Networks by Tree-Structured Learning | Dec 24, 2022 | Uncertainty Quantification | CodeCode Available | 0 |
| Anomaly Detection using Ensemble Classification and Evidence Theory | Dec 23, 2022 | Anomaly DetectionClassification | —Unverified | 0 |
| Parameter Inference based on Gaussian Processes Informed by Nonlinear Partial Differential Equations | Dec 22, 2022 | Gaussian ProcessesUncertainty Quantification | CodeCode Available | 0 |
