In summary, this work introduces Porous-DeepONet, a deep learning framework designed to learn solution operators for parameterized PDEs in porous media, with a focus on reaction-transport equations.

For more than 250 years, mathematicians have been trying to “blow up” some of the most important equations in physics: those that describe how fluids flow. If they succeed, then they will have ...

The recently published book Understanding Deep Learning by [Simon J. D. Prince] is notable not only for focusing primarily on the concepts behind Deep Learning — which should make it highly a… ...

Deep learning focuses on predicting or classifying data, while generative AI creates new content. (Jump to Section) Common deep learning techniques include CNNs, RNNs, and LSTMs.

A Deep Learning Alternative Can Help AI Agents Gameplay the Real World. A new machine learning approach tries to better emulate the human brain, in hopes of creating more capable agentic AI.