Explaining Variational Approximations

نویسندگان
چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود 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

Explaining Variational Approximations

Variational approximations facilitate approximate inference for the parameters in complex statistical models and provide fast, deterministic alternatives to Monte Carlo methods. However, much of the contemporary literature on variational approximations is in Computer Science rather than Statistics, and uses terminology, notation, and examples from the former field. In this article we explain va...

متن کامل

Wild Variational Approximations

We formalise the research problem of approximate inference in the wild: developing new variants of variational methods that work for arbitrary variational approximation families for which inference (e.g., sampling or calculating expectation) is tractable, but probability density function may be intractable. We provide several examples for this type of approximations, discuss energy/gradient app...

متن کامل

Variational Particle Approximations

Monte Carlo methods provide a powerful framework for approximating probability distributions with a set of stochastically sampled particles. In this paper, we rethink particle approximations from the perspective of variational inference, where the particles play the role of variational parameters. This leads to a deterministic version of Monte Carlo in which the particles are selected to optimi...

متن کامل

Grid based variational approximations

Variational methods for approximate Bayesian inference provide fast, flexible, deterministic alternatives to Monte Carlo methods. Unfortunately, unlike Monte Carlo methods, variational approximations cannot, in general, be made to be arbitrarily accurate. This paper develops grid-based variational approximations which endeavor to approximate marginal posterior densities in a spirit similar to t...

متن کامل

On Structured Variational Approximations

The problem of approximating a probability distribution occurs frequently in many areas of applied mathematics including statistics communication theory machine learning and the theoretical analysis of complex systems such as neural networks Saul and Jordan have recently proposed a powerful method for e ciently ap proximating probability distributions known as structured variational approximati...

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: The American Statistician

سال: 2010

ISSN: 0003-1305,1537-2731

DOI: 10.1198/tast.2010.09058