通过奇异性解析的变异贝叶斯神经网络

IF 1.4 2区数学 Q2 STATISTICS & PROBABILITY

Journal of Computational and Graphical Statistics Pub Date : 2024-03-14 DOI:10.1080/10618600.2024.2325455

Susan Wei, Edmund Lau

引用次数: 0

摘要

在这项工作中，我们主张奇异学习理论（SLT）的重要性，因为它涉及贝叶斯神经网络（BNN）中的变异推理理论和实践。首先，我们将...

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Variational Bayesian Neural Networks via Resolution of Singularities

In this work, we advocate for the importance of singular learning theory (SLT) as it pertains to the theory and practice of variational inference in Bayesian neural networks (BNNs). To begin, we la...

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来源期刊

Journal of Computational and Graphical Statistics 数学-统计学与概率论

CiteScore

3.50

自引率

8.30%

发文量

153

审稿时长

>12 weeks

期刊介绍： The Journal of Computational and Graphical Statistics (JCGS) presents the very latest techniques on improving and extending the use of computational and graphical methods in statistics and data analysis. Established in 1992, this journal contains cutting-edge research, data, surveys, and more on numerical graphical displays and methods, and perception. Articles are written for readers who have a strong background in statistics but are not necessarily experts in computing. Published in March, June, September, and December.