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 # POT Releases
 
+## 0.4 Community edition
+
+* Add gromov Wasserstein solver and Gromov Barycenters (PR #23)
+* emd and emd2 can now return dual variables (PR #29) 
+
+## 0.3.1
+*11 Jul 2017*
+
+* Correct bug in emd on windows
+
+## 0.3 Summer release
+*7 Jul 2017*
+
+* emd* and sinkhorn* are now performed in parallel for multiple target distributions
+* emd and sinkhorn are for OT matrix computation
+* emd2 and sinkhorn2 are for OT loss computation
+* new notebooks for emd computation and Wasserstein Discriminant Analysis
+* relocate notebooks
+* update documentation
+* clean_zeros(a,b,M) for removimg zeros in sparse distributions
+* GPU implementations for sinkhorn and group lasso regularization
+
+
+## V0.2 
+*7 Apr 2017*
+
+* New dimensionality reduction method (WDA)
+* Efficient method emd2 returns only tarnsport (in paralell if several histograms given)
+
+
+
 ## V0.1.11 New years resolution
 *5 Jan 2017*
 
@@ -33,10 +64,10 @@
 *28 Oct 2016*
 
 It provides the following solvers:
-* OT solver for the linear program/ Earth Movers Distance [1].
-* Entropic regularization OT solver  with Sinkhorn Knopp Algorithm [2].
-* Bregman projections for Wasserstein barycenter [3] and unmixing [4].
-* Optimal transport for domain adaptation with group lasso regularization [5]
-* Conditional gradient [6] and Generalized conditional gradient for regularized OT [7].
+* OT solver for the linear program/ Earth Movers Distance.
+* Entropic regularization OT solver  with Sinkhorn Knopp Algorithm.
+* Bregman projections for Wasserstein barycenter [3] and unmixing.
+* Optimal transport for domain adaptation with group lasso regularization
+* Conditional gradient and Generalized conditional gradient for regularized OT.
 
 Some demonstrations (both in Python and Jupyter Notebook format) are available in the examples folder.