XDUSPONGE / DeepInfomaxPytorch

Learning deep representations by mutual information estimation and maximization

Deep InfoMax Pytorch

Pytorch implementation of Deep InfoMax https://arxiv.org/abs/1808.06670

Encoding data by maximimizing mutual information between the latent space and in this case, CIFAR 10 images.

Ported most of the code from rcallands chainer implementation. Thanks buddy! https://github.com/rcalland/deep-INFOMAX

Pytorch implementation by the research team here

Current Results (work in progress)

	airplane	automobile	bird	cat	deer	dog	frog	horse	ship	truck
Fully supervised	0.7780	0.8907	0.6233	0.5606	0.6891	0.6420	0.7967	0.8206	0.8619	0.8291
DeepInfoMax-Local	0.6120	0.6969	0.4020	0.4226	0.4917	0.5806	0.6871	0.5806	0.6855	0.5647

Figure 1
Top: a red lamborghini, Middle: 10 closest images in the latent space (L2 distance), Bottom: 10 farthest images in the latent space.

Some more results..