| A least-squares method for sparse low rank approximation of multivariate functions M Chevreuil, R Lebrun, A Nouy, P Rai SIAM/ASA Journal on Uncertainty Quantification 3 (1), 897-921, 2015 | 122 | 2015 |
| Sparse low rank approximation of multivariate functions–Applications in uncertainty quantification P Rai Ecole Centrale de Nantes (ECN), 2014 | 35 | 2014 |
| Detecting technological maturity from bibliometric patterns K Cauthen, P Rai, N Hale, L Freeman, J Ray Expert Systems with Applications 201, 117177, 2022 | 9 | 2022 |
| Sampling based tensor approximation method for uncertainty propagation M Chevreuil, P Rai, A Nouy 11th International Conference on Structural Safety & Reliability-ICOSSAR 2013, 2013 | 9 | 2013 |
| Low-rank canonical-tensor decomposition of potential energy surfaces: application to grid-based diagrammatic vibrational Green's function theory P Rai, K Sargsyan, H Najm, MR Hermes, S Hirata Molecular Physics 115 (17-18), 2120-2134, 2017 | 8 | 2017 |
| Sparse low rank approximation of potential energy surfaces with applications in estimation of anharmonic zero point energies and frequencies P Rai, K Sargsyan, H Najm, S Hirata Journal of Mathematical Chemistry 57, 1732-1754, 2019 | 7 | 2019 |
| A regression based non-intrusive method using separated representation for uncertainty quantification P Rai, M Chevreuil, A Nouy, J Sen Gupta Engineering Systems Design and Analysis 44847, 167-174, 2012 | 3 | 2012 |
| Randomized functional sparse Tucker tensor for compression and fast visualization of scientific data P Rai, H Kolla, L Cannada, A Gorodetsky arXiv preprint arXiv:1907.05884, 2019 | 2 | 2019 |
| Compressed sparse tensor based quadrature for vibrational quantum mechanics integrals P Rai, K Sargsyan, H Najm Computer Methods in Applied Mechanics and Engineering 336, 471-484, 2018 | 2 | 2018 |
| UQTk: A Flexible Python/C++ Toolkit for Uncertainty Quantification. B Debusschere, K Sargsyan, C Safta, P Rai, KS Chowdhary Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2018 | 2 | 2018 |
| A regression based method using sparse low rank approximations for uncertainty propagation P Rai, M Chevreuil, A Nouy, R Lebrun 7th International Conference on Sensitivity Analysis of Model Output-SAMO 2013, 2013 | 2 | 2013 |
| UQTk Version 3.1. 2 User Manual K Sargsyan, C Safta, L Boll, K Johnston, M Khalil, K Chowdhary, P Rai, ... Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2022 | 1 | 2022 |
| Leveraging deep learning algorithms for classification of tomato leaf diseases K Singh, P Rai, K Singla 2021 6th International Conference on Signal Processing, Computing and …, 2021 | 1 | 2021 |
| Achievability Approximation of IDS Hub Using Collaborative Network Model With ML NK Ojha, K Singh, P Rai, A Mourya 2023 IEEE 12th International Conference on Communication Systems and Network …, 2023 | | 2023 |
| ANN classifier for technological maturity based on bibliometric patterns. KR Cauthen, P Rai, J Ray Sandia National Lab.(SNL-NM), Albuquerque, NM (United States); Sandia …, 2020 | | 2020 |
| UQTk User Manual (V. 3.1. 0) K Sargsyan, C Safta, K Johnston, M Khalil, KS Chowdhary, P Rai, ... Sandia National Lab.(SNL-CA), Livermore, CA (United States), 2020 | | 2020 |
| Scalable approximation of Green's function for estimation of anharmonic energy corrections P Rai, K Sargsyan, H Najm, S Hirata arXiv preprint arXiv:1909.06456, 2019 | | 2019 |
| Functional Sparse Tucker Tensor for Scientific Data Compression. P Rai Sandia National Lab.(SNL-CA), Livermore, CA (United States), 2019 | | 2019 |
| Tensors for data science: Concepts Computing and Applications. P Rai Sandia National Lab.(SNL-CA), Livermore, CA (United States), 2019 | | 2019 |
| Learning from data using Functional Tensors. P Rai Sandia National Lab.(SNL-CA), Livermore, CA (United States), 2019 | | 2019 |
