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…