Research map / Learning theory and algorithms / Optimal transport
Sliced Gromov-Wasserstein
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| use SGW instead of GW for computing distances between meshes | horse mesh MDS · horse mesh pairwise distances | time per pair: 30 minutes -> 1.5s | Helped |
| optimize projection Delta on Stiefel manifold (RISGW) instead of fixed identity Delta (ablation) | SGW · rotated spiral dataset | rotation invariance | Helped |
| replace entropic-GW loss with SGW in GW-based GAN | GW generative model · toy 2D/3D generation | time per epoch | Helped |
| replace GW with SGW on large point sets | GW · runtime vs n | scalability | Helped |
Closest papers by meaning
- Statistical and Computational Guarantees of Kernel Max-Sliced Wasserstein Distances (ICML 2025 · similarity 0.91)
- Towards Understanding Gradient Dynamics of the Sliced-Wasserstein Distance via Critical Point Analysis (ICML 2025 · similarity 0.91)
- Differentiable Generalized Sliced Wasserstein Plans (NeurIPS 2025 · similarity 0.90)
- Tree-Sliced Wasserstein Distance with Nonlinear Projection (ICML 2025 · similarity 0.90)
- Distance-Based Tree-Sliced Wasserstein Distance (ICLR 2025 · similarity 0.90)
- Tree-Sliced Wasserstein Distance: A Geometric Perspective (ICML 2025 · similarity 0.89)
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