“physics-free” presumably for it to be a proof of concept, while a more realistic model would probably be a hybrid?
Today at the @ametsoc meeting, we are presenting research into precipitation nowcasting, which focuses on 0-6 hour forecasts with 1 km resolution and only 5-10 minute lag-time, using “physics-free” #MachineLearning models. Learn all about it at https://goo.gle/35SAEdk .pic.twitter.com/7P2ebHh9Kr
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Incorporating prior knowledge on conservation laws or symmetries into the model is very likely to improve its performance since it reduces the hypothesis space 'physically valid' models. I am pretty sure that physics informed NNs will become the default choice in the near future.
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Has the code been released for this?
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Tweet je nedostupan.
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Is that the same approach as by Lebedev et al.? https://arxiv.org/abs/1905.09932 They were using that approach in Russia.
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Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi
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Not possible to be physics free.
Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi
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Get that self learning ai to study all major science topics great one off the start #1 subatomic particles # 2 neuroscience and the human body also see what that AI can do with the quantum computer
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Just wondering will the bottom up approach works as well; I mean if we use a fish eye
and track clouds can we predict weather of near by ?Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi
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Great talk!
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Čini se da učitavanje traje već neko vrijeme.
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