Harness the Model Uncertainty via Hierarchical Weakly Informative Priors in Bayesian Neural Network

نویسندگان

چکیده

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Model Selection in Bayesian Neural Networks via Horseshoe Priors

Bayesian Neural Networks (BNNs) have recently received increasing attention for their ability to provide well-calibrated posterior uncertainties. However, model selection—even choosing the number of nodes—remains an open question. In this work, we apply a horseshoe prior over node preactivations of a Bayesian neural network, which effectively turns off nodes that do not help explain the data. W...

متن کامل

Network inference using informative priors.

Recent years have seen much interest in the study of systems characterized by multiple interacting components. A class of statistical models called graphical models, in which graphs are used to represent probabilistic relationships between variables, provides a framework for formal inference regarding such systems. In many settings, the object of inference is the network structure itself. This ...

متن کامل

Bayesian generalized linear mixed modeling of Tuberculosis using informative priors

TB is rated as one of the world's deadliest diseases and South Africa ranks 9th out of the 22 countries with hardest hit of TB. Although many pieces of research have been carried out on this subject, this paper steps further by inculcating past knowledge into the model, using Bayesian approach with informative prior. Bayesian statistics approach is getting popular in data analyses. But, most ap...

متن کامل

Hierarchical priors for Bayesian CART shrinkage

The Bayesian CART (classiication and regression tree) approach proposed by Chipman, George and McCulloch (1998) entails putting a prior distribution on the set of all CART models and then using stochastic search to select a model. The main thrust of this paper is to propose a new class of hierarchical priors which enhance the potential of this Bayesian approach. These priors indicate a preferen...

متن کامل

Weakly Informative Prior for Covariance Matrices 1 Running head: WEAKLY INFORMATIVE PRIOR FOR COVARIANCE MATRICES Weakly Informative Prior for Point Estimation of Covariance Matrices in Hierarchical Models

When fitting hierarchical regression models, maximum likelihood estimation has computational (and, for some users, philosophical) advantages compared with full Bayesian inference, but when the number of groups is small, estimates of the covariance matrix (Σ) of group-level varying coefficients are often degenerate. One can do better, even from a purely point-estimation perspective, by using a p...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: International Robotics & Automation Journal

سال: 2017

ISSN: 2574-8092

DOI: 10.15406/iratj.2017.03.00057