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Gradients as Features for Deep Representation Learning

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Thanks for this great work! Why jvp has to be calculated via NTK parameterized linear layers? What if just using vanilla Conv2d for the jvp calculation? https://github.com/fmu2/gradfeat20/blob/master/src/model.py#L106

----- Training phase ----- Traceback (most recent call last): File "./src/benchmark.py", line 228, in main() File "./src/benchmark.py", line 219, in main args.niter, args.stepsize, losses, it=it) TypeError: train() missing 1 required...

I tried to run the script, but i cannot use torch.load('name.pt') to load the pre-trained model.