Nuisance hardened data compression for fast likelihood-free inference
نویسندگان
چکیده
منابع مشابه
Likelihood Inference in the Presence of Nuisance Parameters
We describe some recent approaches to likelihood based inference in the presence of nuisance parameters. Our approach is based on plotting the likelihood function and the p-value function, using recently developed third order approximations. Orthogonal parameters and adjustments to profile likelihood are also discussed. Connections to classical approaches of conditional and marginal inference a...
متن کاملELFI: Engine for Likelihood Free Inference
The Engine for Likelihood-Free Inference (ELFI) is a Python software library for performing likelihood-free inference (LFI). ELFI provides a convenient syntax for specifying LFI models commonly composed of priors, simulators, summaries, distances and other custom operations. These can be implemented in a wide variety of languages. Separating the modelling task from the inference makes it possib...
متن کاملLikelihood Almost Free Inference Networks
Variational inference for latent variable models is prevalent in various machine learning problems, typically solved by maximizing the Evidence Lower Bound (ELBO) of the true data likelihood with respect to a variational distribution. However, freely enriching the family of variational distribution is challenging since the ELBO requires variational likelihood evaluations of the latent variables...
متن کاملLikelihood-free inference via classification
Increasingly complex generative models are being used across disciplines as they allow for realistic characterization of data, but a common difficulty with them is the prohibitively large computational cost to evaluate the likelihood function and thus to perform likelihood-based statistical inference. A likelihood-free inference framework has emerged where the parameters are identified by findi...
متن کاملAnalysis of Biological Network Data Using Likelihood-free Inference Techniques
Biological Networks have received much attention in recent years, but statistical tools for network analysis are still in their infancy. In this paper we focus on Protein Interaction Networks (PINs) that typically comprise thousands of proteins and interactions. PINs are the result of long evolutionary histories. Here we adopt simple mathematical models that capture essentials of protein evolut...
متن کاملذخیره 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: Monthly Notices of the Royal Astronomical Society
سال: 2019
ISSN: 0035-8711,1365-2966
DOI: 10.1093/mnras/stz1900