Tutorials¶
Self-contained notebooks that you can run and edit. They are executed at documentation build time, so the outputs in the rendered HTML always match the code.
📓 TDA for beginners
Starts from “what is a filtration” and ends with a diagram-distance comparison of two datasets. For anyone who has heard of persistent homology but hasn’t used it.
📈 Differentiable Wasserstein gradients
Sample a clean and noisy circle, compute differentiable H1 diagrams, and overlay Wasserstein and sliced Wasserstein diagram gradients.
For deeper, task-oriented coverage (filtrations, distances, KICR, Fréchet means, differentiable diagrams, …), see the User guide and the individual Topics essays.