I would like to train a neural operator for the case where I have multiple input functions, an input vector of scalar values and multiple output functions. I tried to implement this using the DeepONet model but I can only use two input functions and I run into errors when I set num_output>1 because I do not know which data shape the model expects.
I came across the Fourier-MIONet paper and this seems to be well suited for my case so I wondered if there is any code available, i.e. a way to implement this fairly easy with this library. Thanks in advance.
I would like to train a neural operator for the case where I have multiple input functions, an input vector of scalar values and multiple output functions. I tried to implement this using the DeepONet model but I can only use two input functions and I run into errors when I set num_output>1 because I do not know which data shape the model expects.
I came across the Fourier-MIONet paper and this seems to be well suited for my case so I wondered if there is any code available, i.e. a way to implement this fairly easy with this library. Thanks in advance.
Best regards Dean