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Simulation By Data ONLY: Fourier Neural Operator (FNO) 

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27 сен 2024

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Комментарии : 8   
@friedrichwilhelmhufnagel3577
@friedrichwilhelmhufnagel3577 5 месяцев назад
Thank you. You are great in preparing one with the apt intuition building being the first stage of understanding the actual math - thanks to the intuition building only a question of "sooner or later" any more. Great talker.
@Dr.Mohammad_Samara
@Dr.Mohammad_Samara 5 месяцев назад
Thank you for your comment, ideas are simple only have some layers that made it seem complex.
@Dr.Mohammad_Samara
@Dr.Mohammad_Samara 18 дней назад
Hope you can enjoy our courses in our Podia platform: Apply "A320" Coupon to get a 25% discount, the first 100 students will get such discount. www.courses.machinedecision.com/
@Dr.Mohammad_Samara
@Dr.Mohammad_Samara 3 месяца назад
Hope you can enjoy our courses in our Podia platform: www.courses.machinedecision.com/
@InoceramusGigas
@InoceramusGigas 3 месяца назад
Great presentation! But i think for viewers it is worth noting that one of the most powerful aspects of the FNO is its ability to learn many timesteps. For example one can provide a single input (initial condition) and have the network output a tensor representing all time steps t0 -> t_end As such it would require that you have representative data available for training, whether it be numerically simulated or experimentally gathered. Great talk
@Dr.Mohammad_Samara
@Dr.Mohammad_Samara 3 месяца назад
Thank you very much for important insight, this video is part of our course about deep neural operator in which we do use the data to build a simulation model using Nvidia Modulus.
@stayinthepursuit8427
@stayinthepursuit8427 2 месяца назад
How does the input picture have timestamps?
@Dr.Mohammad_Samara
@Dr.Mohammad_Samara 2 месяца назад
@@stayinthepursuit8427 it is a bit long story but in short for the deep Neural Operators including the FNO usually we have to pass one image and predict the next (future) time image or solution.
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