Derives a conditional-marginal entropy-rate objective for bridge-aware discretization that yields U-shaped schedules and improves low-NFE sample quality on 2D, CIFAR-10, and protein tasks.
Sinkhorn distances: Lightspeed computation of optimal transport
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
citation-role summary
method 1
citation-polarity summary
years
2026 3roles
method 1polarities
use method 1representative citing papers
A quadratic self-test loss derived from the weak-form evolution equation allows robust learning of particle interaction potentials directly from unlabeled data without trajectory recovery.
FlashSinkhorn delivers up to 32x forward and 161x end-to-end speedups for entropic OT on A100 GPUs via IO-aware Triton kernels that fuse log-domain updates and streaming transport application.
citing papers explorer
-
Learning interacting particle systems from unlabeled data
A quadratic self-test loss derived from the weak-form evolution equation allows robust learning of particle interaction potentials directly from unlabeled data without trajectory recovery.