Tutorials
Interactive Jupyter notebooks covering both the assignment and transport families, from first principles through applied examples.
Interactive Jupyter notebooks for both solver families, targeting readers with Python/PyTorch experience but no prior knowledge of combinatorial optimisation or optimal transport.
Assignment series
| Notebook | Topic |
|---|---|
| The assignment problem | Problem definition, brute-force impossibility, assignment.solve |
| Backends and batching | Backend selection, batched 3-D solve, unpacked output |
| Object tracking | IoU cost matrix, SORT-style tracker, trajectory visualisation |
Transport series
| Notebook | Topic |
|---|---|
| Optimal transport | Earth-mover intuition, transport plans, Wasserstein distance |
| Sinkhorn algorithm | Entropic regularisation, Sinkhorn iterations, divergence |
| Point clouds and shapes | samples.loss, shape generation, unbalanced OT |
Each notebook is also available as a written walkthrough under Assignment tutorials and Transport tutorials.