| Extreme theory of functional connections: A fast physics-informed neural network method for solving ordinary and partial differential equations E Schiassi, R Furfaro, C Leake, M De Florio, H Johnston, D Mortari Neurocomputing 457, 334-356, 2021 | 104 | 2021 |
| Mass loss from calving in Himalayan proglacial lakes CS Watson, JS Kargel, DH Shugar, UK Haritashya, E Schiassi, R Furfaro Frontiers in Earth Science 7, 342, 2020 | 64 | 2020 |
| Fuel-efficient powered descent guidance on large planetary bodies via theory of functional connections H Johnston, E Schiassi, R Furfaro, D Mortari The journal of the astronautical sciences 67 (4), 1521-1552, 2020 | 49 | 2020 |
| Physics-informed neural networks for rarefied-gas dynamics: Thermal creep flow in the Bhatnagar–Gross–Krook approximation M De Florio, E Schiassi, BD Ganapol, R Furfaro Physics of Fluids 33 (4), 2021 | 45 | 2021 |
| Physics-informed neural networks for the point kinetics equations for nuclear reactor dynamics E Schiassi, M De Florio, BD Ganapol, P Picca, R Furfaro Annals of Nuclear Energy 167, 108833, 2022 | 37 | 2022 |
| Physics-informed neural networks and functional interpolation for data-driven parameters discovery of epidemiological compartmental models E Schiassi, M De Florio, A D’Ambrosio, D Mortari, R Furfaro Mathematics 9 (17), 2069, 2021 | 37 | 2021 |
| Physics-informed neural networks and functional interpolation for stiff chemical kinetics M De Florio, E Schiassi, R Furfaro Chaos: An Interdisciplinary Journal of Nonlinear Science 32 (6), 2022 | 32 | 2022 |
| Physics-informed neural networks for optimal planar orbit transfers E Schiassi, A D’Ambrosio, K Drozd, F Curti, R Furfaro Journal of Spacecraft and Rockets 59 (3), 834-849, 2022 | 29 | 2022 |
| Extreme theory of functional connections: A physics-informed neural network method for solving parametric differential equations E Schiassi, C Leake, M De Florio, H Johnston, R Furfaro, D Mortari arXiv preprint arXiv:2005.10632, 2020 | 28 | 2020 |
| Solutions of Chandrasekhar’s basic problem in radiative transfer via theory of functional connections M De Florio, E Schiassi, R Furfaro, BD Ganapol, D Mostacci Journal of quantitative spectroscopy and radiative transfer 259, 107384, 2021 | 25 | 2021 |
| Energy-optimal trajectory problems in relative motion solved via Theory of Functional Connections K Drozd, R Furfaro, E Schiassi, H Johnston, D Mortari Acta Astronautica 182, 361-382, 2021 | 24 | 2021 |
| Pontryagin neural networks with functional interpolation for optimal intercept problems A D’ambrosio, E Schiassi, F Curti, R Furfaro Mathematics 9 (9), 996, 2021 | 23 | 2021 |
| Physics-informed extreme theory of functional connections applied to optimal orbit transfer E Schiassi, A D’Ambrosio, H Johnston, M De Florio, K Drozd, R Furfaro, ... Proceedings of the AAS/AIAA Astrodynamics Specialist Conference, Lake Tahoe …, 2020 | 18 | 2020 |
| Theory of functional connections applied to linear odes subject to integral constraints and linear ordinary integro-differential equations M De Florio, E Schiassi, A D’Ambrosio, D Mortari, R Furfaro Mathematical and computational applications 26 (3), 65, 2021 | 16 | 2021 |
| Theoretical evaluation of anisotropic reflectance correction approaches for addressing multi-scale topographic effects on the radiation-transfer cascade in mountain environments MP Bishop, BW Young, JD Colby, R Furfaro, E Schiassi, Z Chi Remote Sensing 11 (23), 2728, 2019 | 13 | 2019 |
| Complete energy optimal landing on small and large planetary bodies via theory of functional connections E Schiassi, A D’Ambrosio, H Johnston, R Furfaro, F Curti, D Mortari Proceedings of the Astrodynamics Specialist Conference, AAS, South Lake …, 2020 | 12 | 2020 |
| Physics-informed neural networks for rarefied-gas dynamics: Poiseuille flow in the BGK approximation M De Florio, E Schiassi, BD Ganapol, R Furfaro Zeitschrift für angewandte Mathematik und Physik 73 (3), 126, 2022 | 11 | 2022 |
| Physics-informed extreme theory of functional connections applied to data-driven parameters discovery of epidemiological compartmental models E Schiassi, A D'Ambrosio, M De Florio, R Furfaro, F Curti arXiv preprint arXiv:2008.05554, 2020 | 11 | 2020 |
| Physics-Informed Neural Networks for 2nd order ODEs with sharp gradients M De Florio, E Schiassi, F Calabrò, R Furfaro Journal of Computational and Applied Mathematics 436, 115396, 2024 | 9 | 2024 |
| Physics-informed neural networks applied to a series of constrained space guidance problems A D’Ambrosio, E Schiassi, F Curti, R Furfaro AAS/AIAA Astrodynamics Specialist Conference, 2021 | 9 | 2021 |
