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
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..