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[D] Model compression for generative models (GAN, VAE, Autoregressive, etc)

Are there works that investigate VAE and GAN quality, disentanglement, latent variables under model compression constraints? (activations and weights are pruned/sparsed, quantization, distillation, etc)

I can’t seem to find one that apply compression on GANs and VAEs (Exceptions include Parallel WaveNet which do use distillation, but that is because otherwise they can’t get convergence)
Last time we got denoising autoencoders and sparse autoencoders…

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Toronto AI is a social and collaborative hub to unite AI innovators of Toronto and surrounding areas. We explore AI technologies in digital art and music, healthcare, marketing, fintech, vr, robotics and more. Toronto AI was founded by Dave MacDonald and Patrick O'Mara.