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| Improved uncertainty quantification for neural networks with Bayesian last layer | Feb 21, 2023 | Gaussian Processesregression | CodeCode Available | 0 |
| Improved Uncertainty Quantification in Physics-Informed Neural Networks Using Error Bounds and Solution Bundles | May 9, 2025 | parameter estimationUncertainty Quantification | CodeCode Available | 0 |
| Improved User Identification through Calibrated Monte-Carlo Dropout | Sep 29, 2024 | Classifier calibrationUncertainty Quantification | CodeCode Available | 0 |
| Improvements on Uncertainty Quantification for Node Classification via Distance-Based Regularization | Nov 10, 2023 | Node ClassificationOut of Distribution (OOD) Detection | CodeCode Available | 0 |
| Integrating Physics of the Problem into Data-Driven Methods to Enhance Elastic Full-Waveform Inversion with Uncertainty Quantification | Jun 4, 2024 | Deep LearningProbabilistic Deep Learning | CodeCode Available | 0 |
| Efficient Variational Inference for Sparse Deep Learning with Theoretical Guarantee | Nov 15, 2020 | Deep LearningUncertainty Quantification | CodeCode Available | 0 |
| On Calibration of Mixup Training for Deep Neural Networks | Mar 22, 2020 | Data AugmentationUncertainty Quantification | CodeCode Available | 0 |
