| Deep neural network enabled corrective source term approach to hybrid analysis and modeling SS Blakseth, A Rasheed, T Kvamsdal, O San Neural Networks 146, 181-199, 2022 | 36 | 2022 |
| Combining physics-based and data-driven techniques for reliable hybrid analysis and modeling using the corrective source term approach SS Blakseth, A Rasheed, T Kvamsdal, O San Applied Soft Computing 128, 109533, 2022 | 28 | 2022 |
| Unsupervised Anomaly Detection for IoT-Based Multivariate Time Series: Existing Solutions, Performance Analysis and Future Directions MA Belay, SS Blakseth, A Rasheed, P Salvo Rossi Sensors 23 (5), 2844, 2023 | 19 | 2023 |
| Introducing CoSTA: A Deep Neural Network Enabled Approach to Improving Physics-Based Numerical Simulations SS Blakseth NTNU, 2021 | 6 | 2021 |
| Enhancing elasticity models with deep learning: A novel corrective source term approach for accurate predictions S Sørbø, SS Blakseth, A Rasheed, T Kvamsdal, O San Applied Soft Computing 153, 111312, 2024 | | 2024 |
| Enhancing Elasticity Models: A Novel Corrective Source Term Approach for Accurate Predictions S Sørbø, SS Blakseth, A Rasheed, T Kvamsdal, O San arXiv preprint arXiv:2309.10181, 2023 | | 2023 |
| Hybrid Dynamic Surrogate Modelling for a Once-Through Steam Generator SS Blakseth, LE Andersson, RM Montañés, MJ Mazzetti Computer Aided Chemical Engineering 52, 831-836, 2023 | | 2023 |
| Improving Erroneous Physics-Based Models Using the Corrective Source Term Approach S Sørbø, SS Blakseth, A Rasheed, T Kvamsdal, O San Available at SSRN 4269479, 0 | | |
