Physics Informed Neural Networks

A basic introduction to PINNs, or Physics Informed Neural Networks

[@RaviVarma-fo5wm]

Thank you for the simple explanation. At 15:16, is the BC fit term correct? I think it should be [y_hat(1) - y1]^2 in the second term, for x=1?

[@shankyxyz]

interesting but I am truly confused about the ability to solve PDEs. without the accompanying function spaces (sobolev spaces etc) not sure how this is to be taken. it will need extensive explanation of the sobolev space approximation and convergence of solutions theory to be developed. anyways nice explanation. Are you Gautam Kapila from 2002 krec batch?

[@behzadranjbar242]

Thank you very much. Excellent explanation and understanding of PINNs.

[@neerajdoneria9127]

Well explain. Can you plz post any video on hands on building a model with PINN in python.

[@Spiegeldondi]

very structured explanation! makes it easy to grasp the essential concepts!

[@himanshugaur9764]

Thank you. Very clear explanation !!

[@DanielClark-tl5wt]

Awesome video, thanks

[@user-bb6lf4cs3c]

@GautamKapila Do you have an example of notebook using PINN?

[@qwm1007]

Thank you for your clear explanation

[@rainie_876]

Thanks for posting this, what a great explanation!

[@Moonfrog11]

Well explained, thanks

[@vedantgupta6734]

Nice terse explanation!

[@muhammadidrees5218]

Thanks for sharing

[@aidaralimbayev993]

Thanks a lot!

[@nimra4257]

Thabk you for the explanation, but there are many loop holes in the video. In cade of ODE and PDE you have not explained what will be the input , will it be discrete values ? You have not explained the difference between solving an ODE / PDE with PINN and DNN.

[@Weikun-jz2tl]

Thanks

[@douradesh]

would you like to help me solve a inverse heat transfer problem using PINN? send me a message, please

[@nkumarmits]

Do you have LinkedIn profile? please connect

[@blr22]

Good presentation on the subject, Gautam. Are you doing more videos or do you have a suggested playlist on the subject?

[@abhraboral_educator]

HOW ARE THE COLLOCATION POINTS TAKEN

[@saremnoroozi4740]

Excellent explanation!

[@ilyabychkov1166]

Thank you! Perfectly explained!

[@onlyhuman5669]

So clearly explained!

[@turugasairam2886]

great talk

[@alexandren.9346]

I still don't understand what theta stands for. Can someone help?

[@abruptcall]

a vector of the parameters (i.e. weights) of the NN

[@harenderkumar3811]

Great