Jun 21, 2020 · I am following the development of PINNs (Physics Informed Neural Networks) as a mesh-free method to solve PDEs.
Dec 20, 2023 · However, mesh-based methods suffer from the curse of dimensionality, yet the PINN is mesh-free. So PINN is expected to beat traditional solvers ...
Feb 2, 2024 · You can numerically differentiate them without problem, although numerical integration is less reliable due to quadrature errors.
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Feb 27, 2024 · CNNs beat out the densely connected layers because it encodes the idea that features should be translation equivariant (you can move a dog ...
Sure, they present a great unified approach for physics regularized data assimilation, but I could do that aswell with a spectral basis and collocation point ...
Jan 20, 2023 · I learned everything essential to a successful career but didn't learn how to increase our knowledge about nature.
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Mar 22, 2023 · I was watching the GTC keynote and became entirely overwhelmed by the amount of progress achieved from last year. I'm wondering how everyone else feels.
Apr 16, 2014 · I recently proposed a solution to the so-called "black hole information paradox" that only uses known physics, and that completes the framework ...
Jun 20, 2024 · AI models are fed extremely large amounts of data, and essentially spit out the 'statistical average' of said dataset based on a given prompt.
Jun 3, 2016 · The author of the article makes a huge assumption that intelligence requires consciousness. We don't know enough about the relationship of the two to say for ...
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