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Chainer implementation of adversarial autoencoder (AAE)

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![image](https://user-images.githubusercontent.com/25082467/132095743-f965e43d-3adc-4fe3-a7aa-e930525e1bf0.png) The paper mentioned that "The first image in each row shows the cluster heads, which are digits generated by fixing the style variable to zero and setting the label...

Dim_reduction adds a representation part before decoder compared to normal semi-supervised model. However, the inputs of decoders are all addition between tensors, is there any difference? I think normal semi-supervised...

Hello! I use anaconda spyder to compile your perfect project, but I meet some problems. I think it's about my compile environment. I use win7 64bit, and Chainer version is...

Quoting the paper "Once the network is trained, in order to visualize the 10D learnt representation, we use a linear transformation to map the 10D representation to a 2D space...

Since your last commit I get File "run/unsupervised/clustering/train.py", line 180, in main() File "run/unsupervised/clustering/train.py", line 29, in main model = Model() File "/Users/alessandro/adversarial-autoencoder/run/unsupervised/clustering/model.py", line 21, in __init__ nn.Tanh(), File "/Users/alessandro/adversarial-autoencoder/aae/nn.py",...

Hi ,Thanks for your code , I am confused about why you choose the softmax cross entropy , I also tried this loss ,unfortunately , it did work but not...

Hello! Recently, I am studying one of your code about adversarial-autoencoder. I don't know the way that you define the starting labels and ending labels which appears in aae_dim_reduction.py. Could...

Recently, I am studying one of your codes for adversarial-autoencoder. I am supervised at its excellent performance on mnist. Since the original paper also makes the experiment for svhn dataset....

Hi, i just tried your code and found out that it requires scikit-learn package, please update the readme file accordingly. Thank you very much for your contribution.

Hi, I follow the instruction described in paper "Adversarial Autoencoders" to realize the Unsupervised Clustering with Adversarial Autoencoders(section 6). But i didn't get the right cluster result. I want to...