Hi! Welcome to my profile. I'm Ege Demir. I am currently an ML Engineer at Themis AI.
Feel free to contact me via github or from [email protected]
YoanoGAN is a generative adversarial network that uses a discriminator and a generator model to find correct noises to introduce to reduce the accuracy of any arbitrary classification model (with respect to the dataset that it's trained on).
Home Page: http://www.egedemir.me/yoanogan
License: MIT License
Hi! Welcome to my profile. I'm Ege Demir. I am currently an ML Engineer at Themis AI.
Feel free to contact me via github or from [email protected]
Currently, disciminator is outperforming the generator. I believe possible fix to this is by changing the loss function for the generator, which is currently the cross entropy of (1-y_real) and y_pred. This might be counterintuitive because it is hard for generator to be optimized to both decreasing the output of y_real, while increasing the output of every other discriminator neuron
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