Abstract: Physics-informed neural networks (PINNs) offer a flexible framework for solving differential equations using physical constraints and data. This study focuses on second-order ...

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Differential equations are fundamental tools in physics: they are used to describe phenomena ranging from fluid dynamics to general relativity. But when these equations become stiff (i.e. they involve ...

Researchers from the Institute of Cosmos Sciences of the University of Barcelona (ICCUB) have developed a new framework based ...

Physics and Python stuff. Most of the videos here are either adapted from class lectures or solving physics problems. I really like to use numerical calculations without all the fancy programming ...

Free download: Generative AI with Python and PyTorch, Second Edition (worth $38.99) Offered by Wiley, view other free ...

Researchers from the Institute of Cosmos Sciences of the University of Barcelona (ICCUB) have developed a new framework based on machine learning ...

Suzlon Group has secured its FY26 largest order of 838 MW from Tata Power Renewable Energy Limited (TPREL) for its 3 MW series turbines. The order is also its second largest ever. Suzlon stock gained ...

Red Bull team principal Laurent Mekies has explained the different characteristics of the Marina Bay Circuit in Singapore means the team’s “equations” will “move a bit” to find the optimum setup. The ...

A high-performance Python package implementing the Quasi-Steady State (QSS) method for solving stiff ordinary differential equations, with particular focus on combustion chemistry applications. This ...

Abstract: In this paper, a novel approach leveraging artificial neural networks is introduced to approximate solutions for partial differential equations. The one ...