Stein Neural Sampler

8 Oct 2018Tianyang HuZixiang ChenHanxi SunJincheng BaiMao YeGuang Cheng

We propose two novel samplers to produce high-quality samples from a given (un-normalized) probability density. The sampling is achieved by transforming a reference distribution to the target distribution with neural networks, which are trained separately by minimizing two kinds of Stein Discrepancies, and hence our method is named as Stein neural sampler... (read more)

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