条件扩散模型学习跳跃扩散过程转移核

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   arXiv · Statistics Machine Learning

   用条件扩散模型学习跳跃扩散过程的转移核

   研究提出用条件扩散模型学习时齐跳跃扩散过程的转移核，基于高频离散时间网格上观测到的 N 条独立轨迹生成新样本路径。理论上给出条件得分估计误差以及真实与生成路径分布间 KL 散度的非渐近界，数值上在合成数据上验证理论结果并与 Gao et al. (2025) 的方法对标，进一步在真实数据的概率预测任务上检验性能。

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