Hi Pytorch community,
I’ve just coded up a demo of Deep InfoMax. A recently released algorithm from Yoshia Bengio’s research team. https://github.com/DuaneNielsen/DeepInfomaxPytorch
From this paper : Learning deep representations by mutual information estimation and maximization https://arxiv.org/abs/1808.06670
I borrowed heavily from https://github.com/rcalland/deep-INFOMAX, a chainer implementation.
Seems like a promising algorithm to create compressed latent spaces. The basic idea is that you jointly train some loss functions that learn to estimate the amount of mutual information between the latent space and the image. Very cool!