Courses and practical sessions for the Optimal Transport and Machine learning course at Statlearn 2018.
- Introduction to Optimal Transport [PDF]
- Optimization problem
- OT for Machine Learning [PDF]
- Mapping with Optimal Transport
- Learning from histograms with Wasserstein distance
- Learning from empirical distributions with Wasserstein distance
Install Python and POT Toolbox
When anaconda is installed the simplest way to install pot is to launch the anaconda terminal and execute:
conda install -c conda-forge pot
which will install the POT OT Toolbox automatically.
Download the Notebooks for the session
You can download all the necessary files here: OTML_Statlearn2018.zip
The zip file contains the following session:
You can choose to do the practical session using the notebooks included or the python script. We recommend Notebooks for beginners.
The solutions for the practical sessions can be obtained ath the following URL:
Where [NUMBER] has to be replaced by the integer part of the value of the Wasserstein obtained in Practical Session 0 with the Manhattan/Cityblock ground metric.