| Solving inverse problems using conditional invertible neural networks GA Padmanabha, N Zabaras Journal of Computational Physics 433, 110194, 2021 | 72 | 2021 |
| Inverse aerodynamic design of gas turbine blades using probabilistic machine learning S Ghosh, G Anantha Padmanabha, C Peng, V Andreoli, S Atkinson, ... Journal of Mechanical Design 144 (2), 021706, 2022 | 19 | 2022 |
| Pro-ml ideas: A probabilistic framework for explicit inverse design using invertible neural network S Ghosh, GA Padmanabha, C Peng, S Atkinson, V Andreoli, P Pandita, ... AIAA Scitech 2021 Forum, 0465, 2021 | 11 | 2021 |
| A review on data-driven constitutive laws for solids JN Fuhg, GA Padmanabha, N Bouklas, B Bahmani, WC Sun, NN Vlassis, ... arXiv preprint arXiv:2405.03658, 2024 | 7 | 2024 |
| A Bayesian multiscale deep learning framework for flows in random media GA Padmanabha, N Zabaras arXiv preprint arXiv:2103.09056, 2021 | 5 | 2021 |
| Design of optimized two-dimensional scramjet nozzle contour for hypersonic vehicle using evolutionary algorithms A Govinda, MKK Devaraj, Y Singh, N Thakor, VR Kulkarni, SN Omkar, ... 30th International Symposium on Shock Waves 1: ISSW30-Volume 1, 119-124, 2017 | 2 | 2017 |
| Improving the performance of Stein variational inference through extreme sparsification of physically-constrained neural network models GA Padmanabha, JN Fuhg, C Safta, RE Jones, N Bouklas Computer Methods in Applied Mechanics and Engineering 432, 117359, 2024 | | 2024 |
| Deep Learning for Forward and Inverse Solutions of Physical Systems GA Padmanabha University of Notre Dame, 2022 | | 2022 |
| A Probabilistic Machine Learning Framework for Explicit Inverse Design of Industrial Gas Turbine Blades S Ghosh, V Andreoli, GA Padmanabha, C Peng, S Atkinson, P Pandita, ... Turbo Expo: Power for Land, Sea, and Air 85031, V09BT27A003, 2021 | | 2021 |
Nicholas ZabarasProfessor, Cornell UniversityVerified email at nd.edu
