I just read a great post here. I am curious about content of "An example with images" in that post. If the hidden states mean a lot of features of the original picture and getting closer to final result, using dimension reduction on hidden states should provide better result than the original raw pixels, I think.
Hence, I tried it on mnist digits with 2 hidden layers of 256 unit NN, using T-SNE for dimension reduction; the result is far from ideal. From left to right, top to bot, they are raw pixels, second hidden layer and final prediction. Can anyone explain that?
