Jonathan P Williams | DeepAI

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Curtis B Storlie
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Salil Koner
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Terry M Therneau
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Naomi Giertych
2 publications

∙ 07/24/2023

Model-free generalized fiducial inference

Motivated by the need for the development of safe and reliable methods f...

0 Jonathan P Williams, et al. ∙

∙ 02/28/2023

Introduction to Generalized Fiducial Inference

Fiducial inference was introduced in the first half of the 20th century ...

0 Alexander C Murph, et al. ∙

∙ 02/21/2023

Valid Inference for Machine Learning Model Parameters

The parameters of a machine learning model are typically learned by mini...

0 Neil Dey, et al. ∙

∙ 01/17/2023

Word Embeddings as Statistical Estimators

Word embeddings are a fundamental tool in natural language processing. C...

0 Neil Dey, et al. ∙

∙ 11/29/2022

Transfer Learning with Uncertainty Quantification: Random Effect Calibration of Source to Target (RECaST)

Transfer learning uses a data model, trained to make predictions or infe...

0 Jimmy Hickey, et al. ∙

∙ 11/06/2022

Beyond time-homogeneity for continuous-time multistate Markov models

Multistate Markov models are a canonical parametric approach for data mo...

0 Emmett B. Kendall, et al. ∙

∙ 09/30/2022

Generalized Fiducial Inference on Differentiable Manifolds

We introduce a novel approach to inference on parameters that take value...

0 Alexander C Murph, et al. ∙

∙ 05/20/2022

A statistical primer on exoplanet detection methods

Historically, a lack of cross-disciplinary communication has led to the ...

0 Naomi Giertych, et al. ∙

∙ 01/28/2022

A penalized complexity prior for deep Bayesian transfer learning with application to materials informatics

A key task in the emerging field of materials informatics is to use mach...

0 Mohamed A. Abba, et al. ∙

∙ 11/04/2021

Conformal prediction for text infilling and part-of-speech prediction

Modern machine learning algorithms are capable of providing remarkably a...

0 Neil Dey, et al. ∙

∙ 10/11/2021

yaglm: a Python package for fitting and tuning generalized linear models that supports structured, adaptive and non-convex penalties

The yaglm package aims to make the broader ecosystem of modern generaliz...

0 Iain Carmichael, et al. ∙

∙ 10/08/2021

Do Ceasefires Work? A Bayesian autoregressive hidden Markov model to explore how ceasefires shape the dynamics of violence in civil war

Despite a growing body of literature focusing on ceasefires, it is uncle...

0 Jonathan P Williams, et al. ∙

∙ 07/10/2021

The EAS approach to variable selection for multivariate response data in high-dimensional settings

In this paper, we extend the epsilon admissible subsets (EAS) model sele...

0 Salil Koner, et al. ∙

∙ 04/06/2021

Discussion of "A Gibbs sampler for a class of random convex polytopes"

An exciting new algorithmic breakthrough has been advanced for how to ca...

0 Jonathan P Williams, et al. ∙

∙ 12/10/2020

Generalized fiducial factor: an alternative to the Bayes factor for forensic identification of source problems

One formulation of forensic identification of source problems is to dete...

0 Jonathan P Williams, et al. ∙

∙ 06/11/2019

The EAS approach for graphical selection consistency in vector autoregression models

As evidenced by various recent and significant papers within the frequen...

0 Jonathan P Williams, et al. ∙

∙ 07/17/2018

An exposition of the false confidence theorem

A recent paper presents the "false confidence theorem" (FCT) which has p...

0 Iain Carmichael, et al. ∙

∙ 02/08/2018

A Bayesian Approach to Multi-State Hidden Markov Models: Application to Dementia Progression

People are living longer than ever before, and with this arise new compl...

0 Jonathan P Williams, et al. ∙

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