1 code implementation • 21 Dec 2023 • Mario De Florio, Ioannis G. Kevrekidis, George Em Karniadakis
The performance of this framework is validated by recovering the right-hand sides and unknown terms of certain complex, chaotic systems such as the well-known Lorenz system, a six-dimensional hyperchaotic system, and the non-autonomous Sprott chaotic system, and comparing them with their known analytical expressions.
1 code implementation • 29 Sep 2023 • Nazanin Ahmadi Daryakenari, Mario De Florio, Khemraj Shukla, George Em Karniadakis
The proposed framework -- named AI-Aristotle -- combines eXtreme Theory of Functional Connections (X-TFC) domain-decomposition and Physics-Informed Neural Networks (PINNs) with symbolic regression (SR) techniques for parameter discovery and gray-box identification.
no code implementations • 15 May 2020 • Enrico Schiassi, Carl Leake, Mario De Florio, Hunter Johnston, Roberto Furfaro, Daniele Mortari
The proposed method is a synergy of two recently developed frameworks for solving problems involving parametric DEs, 1) the Theory of Functional Connections, TFC, and the Physics-Informed Neural Networks, PINN.