11 citations · 20 across the 2 of their papers we have counts for
3 papers
Physics-Informed Extreme Theory of Functional Connections Applied to Data-Driven Parameters Discovery of Epidemiological Compartmental Models
Enrico Schiassi, Andrea D'Ambrosio, Mario De Florio +2
In this work we apply a novel, accurate, fast, and robust physics-informed neural network framework for data-driven parameters discovery of problems modeled via parametric ordinary…
Extreme Theory of Functional Connections: A Physics-Informed Neural Network Method for Solving Parametric Differential Equations
Enrico Schiassi, Carl Leake, Mario De Florio +3
In this work we present a novel, accurate, and robust physics-informed method for solving problems involving parametric differential equations (DEs) called the Extreme Theory of Fu…
Fuel-Efficient Powered Descent Guidance on Large Planetary Bodies via Theory of Functional Connections
Hunter Johnston, Enrico Schiassi, Roberto Furfaro +1
In this paper we present a new approach to solve the fuel-efficient powered descent guidance problem on large planetary bodies with no atmosphere (e.g. the Moon or Mars) using the…