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1. AdaShift-LGANs-MaxGP-refactored AdaShift-LGANs-MaxGP-refactored Public

   This is a joint implementation of AdaShift optimizer, LGANs, and MaxGP.

   Python 14 2

2. LGANs-for-reproduce LGANs-for-reproduce Public

   This repo is for reproducing our results in “Lipschitz Generative Adversarial Nets”.

   Python 11 3

3. AM-GANs-refactored AM-GANs-refactored Public

   This is a clean implementation of AM-GANs, supporting our paper “Activation Maximization Generative Adversarial Nets”.

   Python 16 1

4. AM-GANs-for-reproduce AM-GANs-for-reproduce Public

   This repo is for reproducing our results in “Activation Maximization Generative Adversarial Nets”.

   Python 11 2

5. MaxGP-MaxAL-for-reproduce MaxGP-MaxAL-for-reproduce Public

   This repo is for reproducing our results on Lipschitz regularization implementations. Tested methods include gradient penalty (GP), spectral normalization (SN), and our proposed MaxGP and MaxAL.

   Python

6. Clustered-Embedding-Learning Clustered-Embedding-Learning Public

   Code for the paper "Clustered Embedding Learning for Recommender Systems"

   Python 9 3