Improving MLP Test accuracy about noise-as-targets-tensorflow HOT 2 OPEN

I suspect an issue with the encoder and the target reassignment because my training loss for the encoder hardly drops under 1

from noise-as-targets-tensorflow.

Thanks for your comments!
Using the convolutional features instead of the learned representation is a good hint, although it is not what the authors claim they do.
Unfortunately, I do not have any further tips for improving the results. I am not one of the authors of the paper and I am not in contact with them. I tried different variations that did not led to improvements and after a while I decided to use adversarial autoencoders instead because they seem to work better for the same task (at least for me).
I plan to upload the tensorflow AAE implementation in the near future.

Regarding the issue: Can you clarify what you mean exactly? Judging by the loss function, the reassignment seems to work well. The loss is dropping fast during the first reassignments.

Regards,
Jan

from noise-as-targets-tensorflow.