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A C# WGAN.

C# 100.00%
wgan gan generative-adversarial-network convolution upscaling mnist number-generator neural-network rmsprop pooling

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mnist-wgan's Issues

Sumlayer Error

Residual errors are being calculated AFTER errors are backpropagated.

Network failing to descend

Basic descent function is nonfunctional. I've added in a test method to have the network operate as a traditional CNN, but even this fails, even when operating stochastically.

So many NaNs

All of the layer types appear to function in isolation (including batchnorm layers), but when I try to stack them bad things happen (NaNs). Need to find and resolve the underlying bug.

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