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..