研究人员推出了一种新颖的切片正则化最优传输（SROT）公式，该公式将传输计划正则化为平滑的切片最优传输计划，比熵最优传输提供了更准确的近似。一种新的Sinkhorn风格算法能够进行高效计算，并保持了可扩展性。在合成数据和颜色迁移任务上的实验表明，SROT在近似精确最优传输计划方面优于现有方法，并在梯度流分析中具有实用性。 AI
影响 引入了改进的最优传输方法，可能增强机器学习和数据分析中的下游应用。
排序理由 该集群包含两篇arXiv论文，介绍了最优传输的新方法。
AI 生成摘要 · Google Gemini · 来自 5 个来源。 我们如何撰写摘要 →
arXiv:2604.23944v1 Announce Type: new Abstract: We propose a new regularized optimal transport (OT) formulation, termed sliced-regularized optimal transport (SROT). Unlike entropic OT (EOT), which regularizes the transport plan toward an independent coupling, SROT regularizes it …
arXiv:2604.24226v1 Announce Type: cross Abstract: In this paper we study continuum-marginal optimal transport. Given a time-continuous family of probability marginals, the problem is to recover the minimum-energy velocity field whose flow reproduces every marginal. This problem i…
In this paper we study continuum-marginal optimal transport. Given a time-continuous family of probability marginals, the problem is to recover the minimum-energy velocity field whose flow reproduces every marginal. This problem is the continuum limit of the classical two-margina…
We propose a new regularized optimal transport (OT) formulation, termed sliced-regularized optimal transport (SROT). Unlike entropic OT (EOT), which regularizes the transport plan toward an independent coupling, SROT regularizes it toward a smoothened sliced OT (SOT) plan. To the…
We propose a new regularized optimal transport (OT) formulation, termed sliced-regularized optimal transport (SROT). Unlike entropic OT (EOT), which regularizes the transport plan toward an independent coupling, SROT regularizes it toward a smoothened sliced OT (SOT) plan. To the…