Overview: Open-source MATLAB libraries help you extend MATLAB’s core functionality with advanced tools for optimization, ...

Jupyter is a way of creating interactive notebooks that blend text, graphics, and code. This is a unique form of programming.

Abstract: By leveraging neural networks, the emerging field of scientific machine learning (SciML) offers novel approaches to address complex problems governed by partial differential equations (PDEs) ...

Abstract: Control of underactuated mechanical systems via energy shaping is a well-established, robust design technique. Unfortunately, its application is often stymied by the need to solve partial ...

We introduce the variational physics informed neural networks – a general framework to solve differential equations. For more information, please refer to the following: Kharazmi, Ehsan, Zhongqiang ...

The course provides a thorough introduction to design, analysis (both theoretical and empirical), and programming of difference and elemental methods to solve differential equations. In addition, the ...

This library provides ordinary differential equation (ODE) solvers implemented in PyTorch. Backpropagation through ODE solutions is supported using the adjoint method for constant memory cost. For ...

We have looked at how to solve equations with one unknown value, but what happens when there are two unknown values? An equation with two unknown values will have infinitely many solutions. or \(x=100 ...