Hybrid physics-informed neural networks for lithium-ion battery modeling and prognosis RG Nascimento, M Corbetta, CS Kulkarni, FAC Viana Journal of Power Sources 513, 230526, 2021 | 142 | 2021 |
A tutorial on solving ordinary differential equations using Python and hybrid physics-informed neural network RG Nascimento, K Fricke, FAC Viana Engineering Applications of Artificial Intelligence 96, 103996, 2020 | 126 | 2020 |
Estimating model inadequacy in ordinary differential equations with physics-informed neural networks FAC Viana, RG Nascimento, A Dourado, YA Yucesan Computers & Structures 245, 106458, 2021 | 80 | 2021 |
Fleet prognosis with physics-informed recurrent neural networks RG Nascimento, FAC Viana arXiv preprint arXiv:1901.05512, 2019 | 75 | 2019 |
Cumulative damage modeling with recurrent neural networks RG Nascimento, FAC Viana AIAA Journal 58 (12), 5459-5471, 2020 | 46 | 2020 |
A framework for Li-ion battery prognosis based on hybrid Bayesian physics-informed neural networks RG Nascimento, FAC Viana, M Corbetta, CS Kulkarni Scientific Reports 13 (1), 13856, 2023 | 18 | 2023 |
Satellite image classification and segmentation with transfer learning R Giorgiani do Nascimento, F Viana Aiaa scitech 2020 forum, 1864, 2020 | 17 | 2020 |
Physics-informed neural networks package FAC Viana, RG Nascimento, Y Yucesan, A Dourado Zenodo. Retrieved from, 2019 | 14 | 2019 |
Quadcopter control optimization through machine learning R Giorgiani do Nascimento, K Fricke, F Viana AIAA Scitech 2020 Forum, 1148, 2020 | 12 | 2020 |
Quadcopter soft vertical landing control with hybrid physics-informed machine learning K Fricke, R Giorgiani do Nascimento, F Viana AIAA Scitech 2021 Forum, 1018, 2021 | 10 | 2021 |
Integrated development environment for analytic authoring AK Subramaniyan, A Iankoulski, RG Do Nascimento US Patent 10,296,296, 2019 | 9 | 2019 |
Li-ion battery aging with hybrid physics-informed neural networks and fleet-wide data RG Nascimento, M Corbetta, CS Kulkarni, FAC Viana Annual conference of the PHM society 13 (1), 2021 | 7 | 2021 |
Usage-based lifing of lithium-ion battery with hybrid physics-informed neural networks R Giorgiani do Nascimento, F Viana, M Corbetta, CS Kulkarni AIAA aviation 2021 forum, 3046, 2021 | 7 | 2021 |
System architecture for secure and rapid development, deployment and management of analytics and software systems AK Subramaniyan, J Lazos, NC KUMAR, A Iankoulski, ... US Patent 10,481,874, 2019 | 7 | 2019 |
Prognosis of li-ion batteries under large load variations using hybrid physics-informed neural networks K Fricke, R Nascimento, M Corbetta, C Kulkarni, F Viana Annual conference of the PHM society 15 (1), 2023 | 6 | 2023 |
Self-aware and self-registering software and analytics platform components AK Subramaniyan, A Iankoulski, RG Do Nascimento US Patent 10,459,774, 2019 | 6 | 2019 |
An accelerated life testing dataset for lithium-ion batteries with constant and variable loading conditions K Fricke, R Nascimento, M Corbetta, C Kulkarni, F Viana International Journal of Prognostics and Health Management 14 (2), 2023 | 3 | 2023 |
Quantifying uncertainty in Li-ion battery aging due to unknown usage with hybrid physics-informed neural networks R Giorgiani do Nascimento, F Viana, M Corbetta, CS Kulkarni AIAA scitech 2023 forum, 0536, 2023 | 3 | 2023 |
Lithium-ion battery prognosis with variational hybrid physics-informed neural networks RG Nascimento University of Central Florida, 2022 | 3 | 2022 |
Systems and methods for optimizing graphics processing for rapid large data visualization AK Subramaniyan, AN Iankoulski, RG do Nascimento US Patent 9,978,114, 2018 | 3 | 2018 |