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| Exploiting the Asymmetric Uncertainty Structure of Pre-trained VLMs on the Unit Hypersphere | May 16, 2025 | Uncertainty Quantification | —Unverified | 0 |
| Calibration and Uncertainty Quantification of Bayesian Convolutional Neural Networks for Geophysical Applications | May 25, 2021 | Bayesian InferenceFault Detection | —Unverified | 0 |
| A Structured Review of Literature on Uncertainty in Machine Learning & Deep Learning | Jun 1, 2024 | Decision MakingDecision Making Under Uncertainty | —Unverified | 0 |
| A Strategy for Adaptive Sampling of Multi-fidelity Gaussian Process to Reduce Predictive Uncertainty | Jul 26, 2019 | 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 |
| A Statistical Machine Learning Approach for Adapting Reduced-Order Models using Projected Gaussian Process | Oct 18, 2024 | Uncertainty Quantification | —Unverified | 0 |
| A Staged Deep Learning Approach to Spatial Refinement in 3D Temporal Atmospheric Transport | Dec 14, 2024 | Super-ResolutionTemporal Sequences | —Unverified | 0 |
| Active Inference or Control as Inference? A Unifying View | Oct 1, 2020 | Uncertainty Quantification | —Unverified | 0 |
