Reviews: Memory Replay GANs: Learning to Generate New Categories without Forgetting

Update following the author rebuttal: I would like to thank the authors for their thoughtful rebuttal. I feel like they appropriately addressed the main points I raised, namely the incomplete evaluation and the choice of GANs over other generative model families, and I'm inclined to recommend the paper's acceptance. I updated my review score accordingly. The paper is well-written and its exposition of the problem, proposed solution, and related work is clear. Starting from the AC-GAN conditional generative modeling formulation, the authors introduce the notion of a sequence of tasks by modeling image classes (for MNIST, SVHN, and LSUN) in sequence, where the model for each class in the sequence is initialized with the model parameters for the previous class in the sequence.