Deep Learning with Yacine on MSN
How to Implement Stochastic Gradient Descent with Momentum in Python
Learn how to implement SGD with momentum from scratch in Python—boost your optimization skills for deep learning.
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 ...
The team has improved the capabilities of physics-informed neural networks (PINNs), a type of artificial intelligence that incorporates physical laws into the learning process. Researchers from the ...
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 ...
Researchers from the Institute of Cosmos Sciences of the University of Barcelona (ICCUB) have developed a new framework based on machine learning ...
Abstract: In this paper, a novel approach leveraging artificial neural networks is introduced to approximate solutions for partial differential equations. The one ...
Abstract: The technique of solving differential equations using Physics-Informed Neural Networks (PINNs) has received extensive attention and application. However, employing neural networks with ...
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