Skip to content

Latest commit

 

History

History
13 lines (9 loc) · 356 Bytes

README.md

File metadata and controls

13 lines (9 loc) · 356 Bytes

GMMILoss

Differentiable Mutual information Loss with pytorch

  1. Train a GM
  2. Estimate MI using covarience matrix (easy)
  3. Consruct a loss function with estimated covarience matrix and means
  4. BackPropagate!

Todo: