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@@ -15,7 +15,8 @@ It provides the following solvers: * OT Network Flow solver for the linear program/ Earth Movers Distance [1]. * Entropic regularization OT solver with Sinkhorn Knopp Algorithm [2] and stabilized version [9][10] with optional GPU implementation (requires cudamat). -* Non regularized Wasserstein barycenters [16] with LP solver. +* Smooth optimal transport solvers (dual and semi-dual) for KL and squared L2 regularizations [17]. +* Non regularized Wasserstein barycenters [16] with LP solver (only small scale). * 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]. @@ -26,12 +27,24 @@ It provides the following solvers: Some demonstrations (both in Python and Jupyter Notebook format) are available in the examples folder. +#### Using and citing the toolbox + +If you use this toolbox in your research and find it useful, please cite POT using the following bibtex reference: +``` +@misc{flamary2017pot, +title={POT Python Optimal Transport library}, +author={Flamary, R{'e}mi and Courty, Nicolas}, +url={https://github.com/rflamary/POT}, +year={2017} +} +``` + ## Installation The library has been tested on Linux, MacOSX and Windows. It requires a C++ compiler for using the EMD solver and relies on the following Python modules: - Numpy (>=1.11) -- Scipy (>=0.17) +- Scipy (>=1.0) - Cython (>=0.23) - Matplotlib (>=1.5) @@ -158,16 +171,7 @@ This toolbox benefit a lot from open source research and we would like to thank * [Nicolas Bonneel](http://liris.cnrs.fr/~nbonneel/) ( C++ code for EMD) * [Marco Cuturi](http://marcocuturi.net/) (Sinkhorn Knopp in Matlab/Cuda) -## Using and citing the toolbox -If you use this toolbox in your research and find it useful, please cite POT using the following bibtex reference: -``` -@article{flamary2017pot, - title={POT Python Optimal Transport library}, - author={Flamary, R{\'e}mi and Courty, Nicolas}, - year={2017} -} -``` ## Contributions and code of conduct Every contribution is welcome and should respect the [contribution guidelines](CONTRIBUTING.md). Each member of the project is expected to follow the [code of conduct](CODE_OF_CONDUCT.md). @@ -216,7 +220,7 @@ You can also post bug reports and feature requests in Github issues. Make sure t [16] Agueh, M., & Carlier, G. (2011). [Barycenters in the Wasserstein space](https://hal.archives-ouvertes.fr/hal-00637399/document). SIAM Journal on Mathematical Analysis, 43(2), 904-924. -[17] Blondel, M., Seguy, V., & Rolet, A. (2018). [Smooth and Sparse Optimal Transport](https://arxiv.org/pdf/1710.06276.pdf). Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics (AISTATS). +[17] Blondel, M., Seguy, V., & Rolet, A. (2018). [Smooth and Sparse Optimal Transport](https://arxiv.org/abs/1710.06276). Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics (AISTATS). [18] Genevay, A., Cuturi, M., Peyré, G. & Bach, F. (2016) [Stochastic Optimization for Large-scale Optimal Transport](arXiv preprint arxiv:1605.08527). Advances in Neural Information Processing Systems (2016). |