资源分类
》 资源 》论文》Yes, but Did It Work?: Evaluating Variational Inference

Yes, but Did It Work?: Evaluating Variational Inference

2020-03-16 | |  40 |   33 |   0

Abstract

While it’s always possible to compute a variational approximation to a posterior distribution, it can be difficult to discover problems with this approximation. We propose two diagnostic algorithms to alleviate this problem. The Paretosmoothed importance sampling (PSIS) diagnostic gives a goodness of fit measurement for joint distributions, while simultaneously improving the error in the estimate. The variational simulationbased calibration (VSBC) assesses the average performance of point estimates.

上一篇：Rates of Convergence of Spectral Methods for Graphon Estimation

下一篇：Visualizing and Understanding Atari Agents

用户评价
全部评价

热门资源

  • Learning to Predi...

    Much of model-based reinforcement learning invo...

  • Stratified Strate...

    In this paper we introduce Stratified Strategy ...

  • The Variational S...

    Unlike traditional images which do not offer in...

  • A Mathematical Mo...

    Direct democracy, where each voter casts one vo...

  • Rating-Boosted La...

    The performance of a recommendation system reli...