| Quantification of deep neural network prediction uncertainties for VVUQ of machine learning models M Yaseen, X Wu Nuclear Science and Engineering 197 (5), 947-966, 2023 | 7 | 2023 |
| Functional PCA and deep neural networks-based Bayesian inverse uncertainty quantification with transient experimental data Z Xie, M Yaseen, X Wu Computer Methods in Applied Mechanics and Engineering 420, 116721, 2024 | 1 | 2024 |
| Fast and accurate reduced-order modeling of a MOOSE-based additive manufacturing model with operator learning M Yaseen, D Yushu, P German, X Wu The International Journal of Advanced Manufacturing Technology 129 (7), 3123 …, 2023 | 1 | 2023 |
| Uncertainty Quantification of Deep Neural Network Predictions for Time-dependent Responses with Functional PCA M Yaseen, Z Xie, X Wu In Proceedings of the 20th International Topical Meeting on Nuclear Reactor …, 2023 | 1 | 2023 |
| Uncertainty Quantification in Deep Neural Network Models for Nuclear Reactor Benchmarks. MQ Yaseen | | 2024 |
| Quantification of Deep Neural Networks Approximation Uncertainties for Transient Simulations MY Xu Wu Transactions of American Nuclear Society. Anaheim, CA, USA. June 12–16, 2022 …, 2022 | | 2022 |
Xu WuAssistant Professor of Nuclear Engineering, North Carolina State UniversityVerified email at ncsu.edu
