Overview: MATLAB books guide students from basic programming to advanced engineering applicationsPractical examples and ...

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: An iterative algorithm to solve periodic Riccati differential equations (PRDE) with an indefinite quadratic term is proposed. In our algorithm, we replace the problem of solving a PRDE with ...

Deep neural networks have garnered widespread attention due to their simplicity and flexibility in the fields of engineering and scientific calculation. In this study ...

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 ...

In January I wrote a piece titled “ 5 Physics Equations Everyone Should Know .” Lots of you weighed in with your own ...

Researchers from the Institute of Industrial Science, The University of Tokyo have applied stochastic optimal control theory ...

This study offers a valuable theoretical framework for quantifying molecular transport across interfaces between coexisting liquid phases, emphasizing interfacial resistance as a central factor ...

A mathematical brain teaser challenges people to solve the matchstick equation in just two moves. The puzzle uses matchsticks ...

We've wondered for centuries whether knowledge is latent and innate or learned and grasped through experience, and a new ...

Mînzu, V. and Arama, I. (2025) A New Method to Predict the Mechanical Behavior for a Family of Composite Materials. Journal ...

The course gives an introduction to analytical techniques for partial differential equations, in particular to separation of variables. In addition the course treats qualititative properties of ...