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Jul, 2018
从聚合数据中学习深层非线性动力学
Learning Deep Hidden Nonlinear Dynamics from Aggregate Data
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Yisen Wang, Bo Dai, Lingkai Kong, Xingjun Ma, Sarah Monazam Erfani...
TL;DR
通过引入具有灵活性的隐藏变量,使用Wasserstein distance的动态生成模型可以从聚合观察数据中直接学习非线性动力学,并且相对于现有技术具有很强的性能表现。
Abstract
Learning
nonlinear dynamics
from
diffusion data
is a challenging problem since the individuals observed may be different at different time points, generally following an aggregate behaviour. Existing work cannot
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