A simple autoencoder to recover MNIST data using convolutional and de-convolutional layers.
Train an AutoEncoder, generate recoverd images, and do t-sne on embeddings.
python main.py
The dimension of embedding is 10
.
Fig.1 and Fig3 in each row are real images
, Fig.2 and Fig.4 in each row are recovered images
.
Epoch 0 | Epoch 5 | Epoch 9 |
---|---|---|
Use t-sne to reduce embeddings' dimension 10
down to 2
, so as to scatter in a coordinate system.