Scientific American

NASA’s Apollo moon missions relied on this computer scientist and differential equations

It’s July 20, 1969. Neil Armstrong and Buzz Aldrin are about to land on the moon. They will be the first humans to set foot on Earth’s only natural satellite. Suddenly, the onboard computer flashes: ...
Frontiers

Implementing physics-informed neural networks with deep learning for differential equations

Physics-aware machine learning integrates domain-specific physical knowledge into machine learning models, leading to the development of physics-informed neural networks (PINNs). PINNs embed physical ...
GitHub

Theory of Functional Connections (TFC)

The tfc Python module is designed to help you quickly and easily apply the Theory of Functional Connections (TFC) to optimization problems. For more information on the code itself and code-based ...
Hacker

Simulating Infectious Disease Spread with Python: SIR and SEIR Models

- Software Engineer - CEO, Lucre (getlucre.xyz - Bitcoin payment infrastructure). Disclaimer: This article aims to clarify that the code provided is not a universal solution for all aspects of ...
GitHub

Runge-Kutta ODE Integrator Implemented in Cython and Numba

CyRK provides fast integration tools to solve systems of ODEs using an adaptive time stepping scheme. CyRK can accept differential equations that are written in pure Python, njited numba, or ...