| Robust Bayesian compressive sensing for signals in structural health monitoring Y Huang, JL Beck, S Wu, H Li Computer‐Aided Civil and Infrastructure Engineering 29 (3), 160-179, 2014 | 89 | 2014 |
| Bayesian compressive sensing for approximately sparse signals and application to structural health monitoring signals for data loss recovery Y Huang, JL Beck, S Wu, H Li Probabilistic Engineering Mechanics 46, 62-79, 2016 | 50 | 2016 |
| General network reliability problem and its efficient solution by Subset Simulation KM Zuev, S Wu, JL Beck Probabilistic Engineering Mechanics 40, 25-35, 2015 | 49 | 2015 |
| Predicting Materials Properties with Little Data Using Shotgun Transfer Learning H Yamada, C Liu, S Wu, Y Koyama, S Ju, J Shiomi, J Morikawa, ... ACS central science 5 (10), 1717-1730, 2019 | 45 | 2019 |
| Machine-learning-assisted discovery of polymers with high thermal conductivity using a molecular design algorithm S Wu, Y Kondo, M Kakimoto, B Yang, H Yamada, I Kuwajima, G Lambard, ... npj Computational Materials 5 (1), 1-11, 2019 | 44 | 2019 |
| A hierarchical Bayesian framework for force field selection in molecular dynamics simulations S Wu, P Angelikopoulos, C Papadimitriou, R Moser, P Koumoutsakos Phil. Trans. R. Soc. A 374 (2060), 20150032, 2016 | 41 | 2016 |
| Bayesian Annealed Sequential Importance Sampling: An Unbiased Version of Transitional Markov Chain Monte Carlo S Wu, P Angelikopoulos, C Papadimitriou, P Koumoutsakos ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B …, 2018 | 33 | 2018 |
| Personalized Radiotherapy Design for Glioblastoma: Integrating Mathematical Tumor Models, Multimodal Scans, and Bayesian Inference J Lipková, P Angelikopoulos, S Wu, E Alberts, B Wiestler, C Diehl, ... IEEE transactions on medical imaging 38 (8), 1875-1884, 2019 | 31* | 2019 |
| ePAD: Earthquake Probability‐Based Automated Decision‐Making Framework for Earthquake Early Warning S Wu, JL Beck, TH Heaton Computer‐Aided Civil and Infrastructure Engineering 28 (10), 737-752, 2013 | 24 | 2013 |
| Fusing heterogeneous data for the calibration of molecular dynamics force fields using hierarchical Bayesian models S Wu, P Angelikopoulos, G Tauriello, C Papadimitriou, P Koumoutsakos The Journal of Chemical Physics 145 (24), 244112, 2016 | 20 | 2016 |
| Virtual Inspector and its application to immediate pre-event and post-event earthquake loss and safety assessment of buildings J Mitrani-Resier, S Wu, JL Beck Natural Hazards 81 (3), 1861-1878, 2016 | 19 | 2016 |
| Earthquake early warning application to buildings MH Cheng, S Wu, TH Heaton, JL Beck Engineering Structures 60, 155-164, 2014 | 17 | 2014 |
| Synergistic combination of systems for structural health monitoring and earthquake early warning for structural health prognosis and diagnosis S Wu, JL Beck Health Monitoring of Structural and Biological Systems 2012 8348, 83481Z, 2012 | 17 | 2012 |
| Multi-events earthquake early warning algorithm using a Bayesian approach S Wu, M Yamada, K Tamaribuchi, JL Beck Geophysical Journal International 200 (2), 791-808, 2015 | 13 | 2015 |
| Fractal dimension based damage identification incorporating multi-task sparse Bayesian learning Y Huang, H Li, S Wu, Y Yang Smart Materials and Structures 27 (7), 075020, 2018 | 12 | 2018 |
| Combining multiple earthquake models in real time for earthquake early warning SE Minson, S Wu, JL Beck, TH Heaton Bulletin of the Seismological Society of America 107 (4), 1868-1882, 2017 | 11 | 2017 |
| Robust Diagnostics for Bayesian Compressive Sensing Technique in Structural Health Monitoring Y Huang, JL Beck, S Wu, H Li Proceedings of the 8th International Workshop on Structural Health …, 2011 | 11 | 2011 |
| A new approach to identify multiple concurrent events for improvement of earthquake early warning K Tamaribuchi, M Yamada, S Wu Zisin 67 (2), 2014 | 9* | 2014 |
| Optimal Sampling Placement in a Gaussian Random Field Based on Value of Information I Yoshida, Y Tasaki, Y Otake, S Wu ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A …, 2018 | 8 | 2018 |
| Hierarchical Stochastic Model in Bayesian Inference for Engineering Applications: Theoretical Implications and Efficient Approximation S Wu, P Angelikopoulos, JL Beck, P Koumoutsakos ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B …, 2019 | 7 | 2019 |
James L. BeckG.W. Housner Professor of Engineering & Applied Science, Emeritus, CaltechVerified email at caltech.edu
