k-diffusion
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Use of DCT in loss function?
I am wondering why in layers.py, the DCT is used like so: sq_error = dct(model_output - target) ** 2 In contrast to many other diffusion model papers where the loss is simply something like the MSE with a weighting factor? How does this impact the training process?