| Phase identification in electric power distribution systems by clustering of smart meter data W Wang, N Yu, B Foggo, J Davis, J Li 2016 15th IEEE International Conference on Machine Learning and Applications …, 2016 | 111 | 2016 |
| A physically inspired data-driven model for electricity theft detection with smart meter data Y Gao, B Foggo, N Yu IEEE Transactions on Industrial Informatics 15 (9), 5076-5088, 2019 | 95 | 2019 |
| Stochastic valuation of energy storage in wholesale power markets N Yu, B Foggo Energy Economics 64, 177-185, 2017 | 70 | 2017 |
| Improved battery storage valuation through degradation reduction B Foggo, N Yu IEEE Transactions on Smart Grid 9 (6), 5721-5732, 2017 | 67 | 2017 |
| GaSb thermophotovoltaic cells grown on GaAs by molecular beam epitaxy using interfacial misfit arrays BC Juang, RB Laghumavarapu, BJ Foggo, PJ Simmonds, A Lin, B Liang, ... Applied Physics Letters 106 (11), 2015 | 51 | 2015 |
| Power system event identification based on deep neural network with information loading J Shi, B Foggo, N Yu IEEE Transactions on Power Systems 36 (6), 5622-5632, 2021 | 50 | 2021 |
| Improving supervised phase identification through the theory of information losses B Foggo, N Yu IEEE Transactions on Smart Grid 11 (3), 2337-2346, 2019 | 42 | 2019 |
| Data driven predictive maintenance of distribution transformers F Kabir, B Foggo, N Yu 2018 China international conference on electricity distribution (CICED), 312-316, 2018 | 36 | 2018 |
| A comprehensive evaluation of supervised machine learning for the phase identification problem B Foggo, N Yu International Journal of Computer and Systems Engineering 12 (6), 419-427, 2018 | 31 | 2018 |
| Online event detection in synchrophasor data with graph signal processing J Shi, B Foggo, X Kong, Y Cheng, N Yu, K Yamashita 2020 IEEE International conference on communications, control, and computing …, 2020 | 28 | 2020 |
| Online power system event detection via bidirectional generative adversarial networks Y Cheng, N Yu, B Foggo, K Yamashita IEEE Transactions on Power Systems 37 (6), 4807-4818, 2022 | 16 | 2022 |
| Online PMU missing value replacement via event-participation decomposition B Foggo, N Yu IEEE Transactions on Power Systems 37 (1), 488-496, 2021 | 16 | 2021 |
| Dynamic parameter estimation with physics-based neural ordinary differential equations X Kong, K Yamashita, B Foggo, N Yu 2022 IEEE Power & Energy Society General Meeting (PESGM), 1-5, 2022 | 8 | 2022 |
| Information losses in neural classifiers from sampling B Foggo, N Yu, J Shi, Y Gao IEEE transactions on neural networks and learning systems 31 (10), 4073-4083, 2019 | 8* | 2019 |
| Online voltage event detection using synchrophasor data with structured sparsity-inducing norms X Kong, B Foggo, K Yamashita, N Yu IEEE Transactions on Power Systems 37 (5), 3506-3515, 2021 | 6 | 2021 |
| On the maximum mutual information capacity of neural architectures B Foggo, N Yu arXiv preprint arXiv:2006.06037, 2020 | 6 | 2020 |
| pmuBAGE: The Benchmarking Assortment of Generated PMU Data for Power System Events B Foggo, K Yamashita, N Yu arXiv preprint arXiv:2210.14204, 2022 | 5 | 2022 |
| Missing value replacement for pmu data via deep learning model with magnitude trend decoupling Y Cheng, B Foggo, K Yamashita, N Yu IEEE Access 11, 27450-27461, 2023 | 3 | 2023 |
| Analyzing data selection techniques with tools from the theory of information losses B Foggo, N Yu 2021 IEEE International Conference on Big Data (Big Data), 7-16, 2021 | 2 | 2021 |
| Interpreting active learning methods through information losses B Foggo, N Yu arXiv preprint arXiv:1902.09602, 95, 2019 | 2 | 2019 |
Nanpeng YuUniversity of California, RiversideDirección de correo verificada de ece.ucr.edu
