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Coding Exercise on Barlow Twins

Explore how to implement the Barlow Twins loss function for self-supervised learning by mean-centering embeddings, computing correlation matrices, and balancing redundancy reduction with similarity maximization. This lesson helps you develop hands-on skills to optimize representations from augmented data views.

The Barlow Twins objective function

Given the representations of distorted views of a batch, Z1Z_1 and Z2Z_2, and assuming they are mean-centered (zero mean and unit variance) along the batch, the Barlow Twins algorithm first computes a correlation matrix C\mathcal{C} with ...