activity
20172023
most citedDeep Theory of Functional Connections: A New Method for Estimating the Solutions of PDEs

88 citations · 382 across the 20 of their papers we have counts for

collaborators

20 papers

astro-ph.IM2023★ 8 cited

Orbit transfer using Theory of Functional Connections via change of variables

Allan K. de Almeida, Antonio F. B. A. Prado, Daniele Mortari

This work shows that a class of astrodynamics problems subject to mission constraints can be efficiently solved using the Theory of Functional Connections (TFC) mathematical framew…

astro-ph.EP2021★ 20 cited

Fast 2-impulse non-Keplerian orbit-transfer using the Theory of Functional Connections

Allan K. de Almeida Junior, Hunter Johnston, Carl Leake +1

This study applies a new approach, the Theory of Functional Connections (TFC), to solve the two-point boundary-value problem (TPBVP) in non-Keplerian orbit transfer. The perturbati…

math.NA2020★ 45 cited

The Multivariate Theory of Functional Connections: Theory, Proofs, and Application in Partial Differential Equations

Carl Leake, Hunter Johnston, Daniele Mortari

This article presents a reformulation of the Theory of Functional Connections: a general methodology for functional interpolation that can embed a set of user-specified linear cons…

math.NA2020

Bijective Mapping Analysis to Extend the Theory of Functional Connections to Non-rectangular 2-dimensional Domains

Daniele Mortari, David Anas

This work presents an initial analysis of using bijective mappings to extend the Theory of Functional Connections to non-rectangular two-dimensional domains. Specifically, this man…

cs.LG2020★ 11 cited

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…

cs.DS2020★ 6 cited

Nonlinear Function Inversion using k-vector

David Arnas, Daniele Mortari

This work introduces a general numerical technique to invert one dimensional analytic or tabulated nonlinear functions in assigned ranges of interest. The proposed approach is base…