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Is there any way to approximate embeddings for a novel image?

novel meaning user provided, not generated by the model or in the training set.

Not at the moment in our tool, though this is an area of great curiosity and research for us!

Does the discriminator model translate the images into an embedding space of it's own? Could such a space be used to generate images themselves?