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add images and begin releases file
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README.md

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@@ -123,6 +123,10 @@ Here is a list of the Python notebooks available [here](https://github.com/rflam
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* [OT mapping estimation for domain adaptation](https://github.com/rflamary/POT/blob/master/notebooks/plot_otda_mapping.ipynb)
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* [OT mapping estimation for color transfer in images](https://github.com/rflamary/POT/blob/master/notebooks/plot_otda_mapping_colors_images.ipynb)
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* [Wasserstein Discriminant Analysis](https://github.com/rflamary/POT/blob/master/notebooks/plot_WDA.ipynb)
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* [Gromov Wasserstein](https://github.com/rflamary/POT/blob/master/notebooks/plot_gromov.ipynb)
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* [Gromov Wasserstein Barycenter](https://github.com/rflamary/POT/blob/master/notebooks/plot_gromov_barycenter.ipynb)
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You can also see the notebooks with [Jupyter nbviewer](https://nbviewer.jupyter.org/github/rflamary/POT/tree/master/notebooks/).
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RELEASES.md

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# POT Releases
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## V0.1.11 New years resolution
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*5 Jan 2017*
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* Add sphinx gallery for better documentation
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* Small efficiency tweak in sinkhorn
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* Add simple tic() toc() functions for timing
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## V0.1.10
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*7 Nov 2016*
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* numerical stabilization for sinkhorn (log domain and epsilon scaling)
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## V0.1.9 DA classes and mapping
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*4 Nov 2016*
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* Update classes and examples for domain adaptation
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* Joint OT matrix and mapping estimation
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## V0.1.7
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*31 Oct 2016*
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* Original Domain adaptation classes
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## PyPI version 0.1.3
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* pipy works
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## First pre-release
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*28 Oct 2016*
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It provides the following solvers:
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* OT solver for the linear program/ Earth Movers Distance [1].
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* Entropic regularization OT solver with Sinkhorn Knopp Algorithm [2].
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* Bregman projections for Wasserstein barycenter [3] and unmixing [4].
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* Optimal transport for domain adaptation with group lasso regularization [5]
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* Conditional gradient [6] and Generalized conditional gradient for regularized OT [7].
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Some demonstrations (both in Python and Jupyter Notebook format) are available in the examples folder.
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