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> Topological transformation of the manifold happens during training too. That makes me wonder: how does the topology evolve during training?

If you've ever played with GANs or VAEs, you can actually answer this question! And the answer is more or less 'yes'. You can look at GANs at various checkpoints during training and see how different points in the high dimensional space move around (using tools like UMAP / TSNE).

> I imagine it violently changing at first before stabilizing, followed by geometric refinement

Also correct, though the violent changing at the beginning is also influenced the learning rate and the choice of optimizer.



And crucially, the initialization algorithm.




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