Progress and prospects of artificial intelligence development and applications in supersonic flow and combustion
J Le, M Yang, M Guo, Y Tian, H Zhang - Progress in Aerospace Sciences, 2024 - Elsevier
Due to the significant improvement in computing power and the rapid advancement of data
processing technologies, artificial intelligence (AI) has introduced new tools and …
processing technologies, artificial intelligence (AI) has introduced new tools and …
Training stiff neural ordinary differential equations with implicit single-step methods
Stiff systems of ordinary differential equations (ODEs) are pervasive in many science and
engineering fields, yet standard neural ODE approaches struggle to learn them. This …
engineering fields, yet standard neural ODE approaches struggle to learn them. This …
Bayesian polynomial neural networks and polynomial neural ordinary differential equations
Symbolic regression with polynomial neural networks and polynomial neural ordinary
differential equations (ODEs) are two recent and powerful approaches for equation recovery …
differential equations (ODEs) are two recent and powerful approaches for equation recovery …
Training Stiff Neural Ordinary Differential Equations with Explicit Exponential Integration Methods
Stiff ordinary differential equations (ODEs) are common in many science and engineering
fields, but standard neural ODE approaches struggle to accurately learn these stiff systems …
fields, but standard neural ODE approaches struggle to accurately learn these stiff systems …
Prior knowledge meets neural ODEs: a two-stage training method for improved explainability
Neural Ordinary Differential Equations (ODEs) have been used extensively to model
physical systems because they represent a continuous-time function that can make …
physical systems because they represent a continuous-time function that can make …
A Self-Adaptive Penalty Method for Integrating Prior Knowledge Constraints into Neural ODEs
The continuous dynamics of natural systems has been effectively modelled using Neural
Ordinary Differential Equations (Neural ODEs). However, for accurate and meaningful …
Ordinary Differential Equations (Neural ODEs). However, for accurate and meaningful …
Back to the Roots: A Suite of Xai Techniques for Understanding Neural Ordinary Differential Equations
Abstract Neural Ordinary Differential Equations (Neural ODEs) have emerged as a
promising approach for learning continuous-time functions from data using an ODE, offering …
promising approach for learning continuous-time functions from data using an ODE, offering …