SOURCE-LINKED INTELLIGENCE
Dynamic Generalized Gromov-Wasserstein Optimal Transport
Gromov--Wasserstein optimal transport (GW-OT) extends classical optimal transport by introducing structure-aware transport cost. This is particularly relevant for spatial transcriptomics, where dynamical reconstruction should preserve tissue structure in addition to matching expression patterns. While static formulations have been widely used for such structure-aware alignment, a general dynamic formulation for reconstructing continuous trajectories is still missing. We introduce Travelling Pair Dynamical Alignment and Trajectory Estimation (TP-DATE), a theoretical and computational framework
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Evidence & attribution
- arXiv · Artificial Intelligence · 2026-09-17T10:17:33.000Z
- arXiv · AI, language, vision and robotics · 2026-09-17T10:17:33.000Z
First collected: 2026-09-19T20:26:32.566Z. This is not the publication date.