Comments (1)
You train the second DAE with the first DAE's encoded as input.
Second DAE tries to reconstruct the first DAE's encoded by performing it's own encoding followed by decoding.
Your second DAE's loss is therefore LOSS(second DAE's decoded, 1st DAE's encoded)
from libsdae-autoencoder-tensorflow.
Related Issues (11)
- Error in Mini Batch HOT 4
- Other dataset than mnist HOT 2
- UnboundLocalError: local variable 'l' referenced before assignment (at stacked_autoencoder.py#L128) HOT 1
- Content of data/ in top directory HOT 3
- Saving and restoring the model
- utils missing HOT 1
- Cannot get cross-entropy to work HOT 14
- How to decode the transform result? HOT 7
- AutoEncoder Graph Construction HOT 3
- Blas GEMM launch failed HOT 3
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from libsdae-autoencoder-tensorflow.