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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.

Jousef Murad

19,926 subscribers

433,240 görüntüleme • 2 yıl önce •via X (Twitter)

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Jousef Murad profil fotoğrafı

Jousef Murad2 yıl önce

🌎 Repo: 👉 Paper:

Luke Barnes profil fotoğrafı

Luke Barnes2 yıl önce

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.

Rasmus Nordström profil fotoğrafı

Rasmus Nordström2 yıl önce

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

Moritz Zaiss profil fotoğrafı

Moritz Zaiss2 yıl önce

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

Jiwoong Lee profil fotoğrafı

Jiwoong Lee2 yıl önce

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

Luis Tobon profil fotoğrafı

Luis Tobon2 yıl önce

Try Sindy.

Wassim Tenachi profil fotoğrafı

Wassim Tenachi2 yıl önce

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

Unser Kampf : notre combat profil fotoğrafı

Unser Kampf : notre combat2 yıl önce

How many points are tested ? 4k+1 ?

Unser Kampf : notre combat profil fotoğrafı

Unser Kampf : notre combat2 yıl önce

Il like very much. Your works completes mine.

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