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Φ-SO : Physical Symbolic Optimization - Learning Physics from Data 🧠 The Physical Symbolic Optimization package uses deep reinforcement learning to discover physical laws from data. Here is Φ-SO discovering the analytical expression of a damped harmonic oscillator.

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Jousef Murad

19,846 subscribers

433,091 просмотров • 2 лет назад •via X (Twitter)

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Комментарии: 9

Фото профиля Jousef Murad
Jousef Murad2 лет назад

🌎 Repo:  👉 Paper: 

Фото профиля Luke Barnes
Luke Barnes2 лет назад

This isn't physics. It's curve fitting. If you want to do physics, start by having the code discover the underlying differential equation. Handy, though.

Фото профиля Rasmus Nordström
Rasmus Nordström2 лет назад

ELI5 please, is this just brute forcing different formulas to see what fits that data or is it more magic to it?

Фото профиля Moritz Zaiss
Moritz Zaiss2 лет назад

Nice, I love these approaches! A differentiable physicist that doesn't need coffee. Check out the work of @GMartius in this context!

Фото профиля Jiwoong Lee
Jiwoong Lee2 лет назад

Would it be more straightforward to optimize in frequency domain? Curious.

Фото профиля Luis Tobon
Luis Tobon2 лет назад

Try Sindy.

Фото профиля Wassim Tenachi
Wassim Tenachi2 лет назад

Thanks for sharing my work, glad to see people excited about this ! 😊

Фото профиля Unser Kampf : notre combat
Unser Kampf : notre combat2 лет назад

How many points are tested ? 4k+1 ?

Фото профиля Unser Kampf : notre combat
Unser Kampf : notre combat2 лет назад

Il like very much. Your works completes mine.

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