English(EN) Schr\"odinger Bridges on Lie Group Manifolds for Probabilistic Intrinsic Generation

新的Schrödinger Bridges框架支持在几何流形上进行生成建模

作者 PulseAugur 编辑部 · [1 个来源] · 2026-09-03 04:00

研究人员开发了一个名为Schrödinger Bridges的新概率生成框架，该框架设计用于直接在几何流形上运行。该方法旨在通过避免与展平非欧几里得数据相关的错误并保持坐标一致性来改进生成建模。该框架利用指定端点分布之间的熵正则化传输，并有两种计算实现方式：用于紧凑阿贝尔群的Wrapped-Kernel Bridge Calibration (WKBC) 和用于紧凑非阿贝尔群的Reciprocal Conditional-Control Bridge Matching (RCCBM)。在包括蛋白质和RNA扭转在内的各种数据集上的实验证明了该方法的可行性和一致性。 AI

影响引入了一种在复杂几何数据上进行生成建模的新颖方法，有可能改进分子动力学和结构生物学等领域的应用。

排序理由详细介绍新生成建模框架的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv stat.ML 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。我们如何撰写摘要 →

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报道来源 [1]

arXiv stat.ML TIER_1 English(EN) · Shizhe Zhang, Mingyang Zhao, Lei Ma · 2026-09-03 04:00

Schrödinger在李群流形上进行概率内在生成

arXiv:2609.02196v1 Announce Type: new Abstract: Generative modeling directly on geometric manifolds can avoid errors introduced by flattening non-Euclidean data, repeated ambient projection, and coordinate inconsistency in Euclidean representations. Schrodinger bridges provide a …

本文如何被排名

报道来源 [1]

Schrödinger在李群流形上进行概率内在生成

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