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diff --git a/docs/source/quickstart.rst b/docs/source/quickstart.rst index 09a362b..b4cc8ab 100644 --- a/docs/source/quickstart.rst +++ b/docs/source/quickstart.rst @@ -1028,15 +1028,6 @@ FAQ speedup can be obtained by using a GPU implementation since all operations are matrix/vector products. -4. **Using GPU fails with error: module 'ot' has no attribute 'gpu'** - - In order to limit import time and hard dependencies in POT. we do not import - some sub-modules automatically with :code:`import ot`. In order to use the - acceleration in :any:`ot.gpu` you need first to import is with - :code:`import ot.gpu`. - - See `Issue #85 <https://github.com/rflamary/POT/issues/85>`__ and :any:`ot.gpu` - for more details. References @@ -1172,3 +1163,52 @@ References .. [30] Flamary, Rémi, et al. "Optimal transport with Laplacian regularization: Applications to domain adaptation and shape matching." NIPS Workshop on Optimal Transport and Machine Learning OTML. 2014. + +.. [31] Bonneel, Nicolas, et al. `Sliced and radon wasserstein barycenters of + measures + <https://perso.liris.cnrs.fr/nicolas.bonneel/WassersteinSliced-JMIV.pdf>`_\ + , Journal of Mathematical Imaging and Vision 51.1 (2015): 22-45 + +.. [32] Huang, M., Ma S., Lai, L. (2021). `A Riemannian Block Coordinate Descent Method for Computing the Projection Robust Wasserstein Distance <http://proceedings.mlr.press/v139/huang21e.html>`_\ , Proceedings of the 38th International Conference on Machine Learning (ICML). + +.. [33] Kerdoncuff T., Emonet R., Marc S. `Sampled Gromov Wasserstein + <https://hal.archives-ouvertes.fr/hal-03232509/document>`_\ , Machine + Learning Journal (MJL), 2021 + +.. [34] Feydy, J., Séjourné, T., Vialard, F. X., Amari, S. I., Trouvé, A., & + Peyré, G. (2019, April). `Interpolating between optimal transport and MMD + using Sinkhorn divergences + <http://proceedings.mlr.press/v89/feydy19a/feydy19a.pdf>`_. In The 22nd + International Conference on Artificial Intelligence and Statistics (pp. + 2681-2690). PMLR. + +.. [35] Deshpande, I., Hu, Y. T., Sun, R., Pyrros, A., Siddiqui, N., Koyejo, S., + & Schwing, A. G. (2019). `Max-sliced wasserstein distance and its use + for gans + <https://openaccess.thecvf.com/content_CVPR_2019/papers/Deshpande_Max-Sliced_Wasserstein_Distance_and_Its_Use_for_GANs_CVPR_2019_paper.pdf>`_. + In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 10648-10656). + +.. [36] Liutkus, A., Simsekli, U., Majewski, S., Durmus, A., & Stöter, F. R. + (2019, May). `Sliced-Wasserstein flows: Nonparametric generative modeling via + optimal transport and diffusions + <http://proceedings.mlr.press/v97/liutkus19a/liutkus19a.pdf>`_. In International + Conference on Machine Learning (pp. 4104-4113). PMLR. + +.. [37] Janati, H., Cuturi, M., Gramfort, A. `Debiased sinkhorn barycenters + <http://proceedings.mlr.press/v119/janati20a/janati20a.pdf>`_ Proceedings of + the 37th International Conference on Machine Learning, PMLR 119:4692-4701, 2020 + +.. [38] C. Vincent-Cuaz, T. Vayer, R. Flamary, M. Corneli, N. Courty, `Online + Graph Dictionary Learning <https://arxiv.org/pdf/2102.06555.pdf>`_\ , + International Conference on Machine Learning (ICML), 2021. + +.. [39] Gozlan, N., Roberto, C., Samson, P. M., & Tetali, P. (2017). + `Kantorovich duality for general transport costs and applications + <https://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.712.1825&rep=rep1&type=pdf>`_. + Journal of Functional Analysis, 273(11), 3327-3405. + +.. [40] Forrow, A., Hütter, J. C., Nitzan, M., Rigollet, P., Schiebinger, G., & + Weed, J. (2019, April). `Statistical optimal transport via factored + couplings <http://proceedings.mlr.press/v89/forrow19a/forrow19a.pdf>`_. In + The 22nd International Conference on Artificial Intelligence and Statistics + (pp. 2454-2465). PMLR. |