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gradientpathologiespinns's Issues

Gradient for loss function

Dear Sir
I found your paper which is very interesting and useful. and I am trying to implement the dynamic coefficient according to the first method you have introduced. I am wondering in practice how to implement the gradient of the loss. I have tried auto differentiation like:
tf.gradients(loss,weight)
But I don't know whether it is the one for your definition.

thanks for replying

TF2 GPU

Dear Sir,

I would like to say the idea behind your work is impressive!
However, because of TF2 update, your code is not GPU supported any more! (Due to "placeholder" and "tf.session").
Have you updated your code to be GPU supported?
I've tried to do that but I face problems...

Klein_Gordon_model with supervised learning!

In Klein_Gordon_model_tf.py, line 108, you used supervised learning in the domain to get the difference between the output of the neural network and actual results during training.

self.loss_res = tf.reduce_mean(tf.square(self.r_pred - self.r_tf))

The same thing happened to elmholtz2D_model_tf.py line 106
self.loss_res = tf.reduce_mean(tf.square(self.r_tf - self.r_pred))
What is the use of physics in this case?

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