Jonathan Huggins

Jonathan Huggins

Boston University

H-index: 18

North America-United States

About Jonathan Huggins

Jonathan Huggins, With an exceptional h-index of 18 and a recent h-index of 16 (since 2020), a distinguished researcher at Boston University, specializes in the field of Bayesian computation, Large-scale learning, Robust inference, Machine Learning.

His recent articles reflect a diverse array of research interests and contributions to the field:

Structurally Aware Robust Model Selection for Mixtures

Reproducible parameter inference using bagged posteriors

Bayesian Analysis

Independent finite approximations for Bayesian nonparametric inference

A Targeted Accuracy Diagnostic for Variational Approximations

Reproducible model selection using bagged posteriors

Statistical inference with stochastic gradient algorithms

Tuning Stochastic Gradient Algorithms for Statistical Inference via Large-Sample Asymptotics

Jonathan Huggins Information

University

Position

Assistant Professor of Statistics

Citations(all)

952

Citations(since 2020)

792

Cited By

438

hIndex(all)

18

hIndex(since 2020)

16

i10Index(all)

23

i10Index(since 2020)

19

Email

University Profile Page

Boston University

Google Scholar

View Google Scholar Profile

Jonathan Huggins Skills & Research Interests

Bayesian computation

Large-scale learning

Robust inference

Machine Learning

Top articles of Jonathan Huggins

Title

Journal

Author(s)

Publication Date

Structurally Aware Robust Model Selection for Mixtures

arXiv preprint arXiv:2403.00687

Jiawei Li

Jonathan H Huggins

2024/3/1

Reproducible parameter inference using bagged posteriors

Electronic Journal of Statistics

Jonathan H Huggins

Jeffrey W Miller

2024

Bayesian Analysis

Bayesian Analysis

FO Bunnin

JQ Smith

F Ruggeri

M Sánchez-Sánchez

MÁ Sordo

...

2021

Independent finite approximations for Bayesian nonparametric inference

Bayesian Analysis

Tin D Nguyen

Jonathan Huggins

Lorenzo Masoero

Lester Mackey

Tamara Broderick

2023/1

A Targeted Accuracy Diagnostic for Variational Approximations

Yu Wang

Mikolaj Kasprzak

Jonathan H Huggins

2023/4/11

Reproducible model selection using bagged posteriors

Bayesian analysis

Jonathan H Huggins

Jeffrey W Miller

2023/3

Statistical inference with stochastic gradient algorithms

arXiv preprint arXiv

Jeffrey Negrea

Jun Yang

Haoyue Feng

Daniel M Roy

Jonathan H Huggins

2022/11/14

Tuning Stochastic Gradient Algorithms for Statistical Inference via Large-Sample Asymptotics

arXiv preprint arXiv:2207.12395

Jeffrey Negrea

Jun Yang

Haoyue Feng

Daniel M Roy

Jonathan H Huggins

2022/7/25

Robust, automated, and accurate black-box variational inference

arXiv preprint arXiv:2203.15945

Manushi Welandawe

Michael Riis Andersen

Aki Vehtari

Jonathan H Huggins

2022/3/29

Calibrated model criticism using split predictive checks

arXiv preprint arXiv:2203.15897

Jiawei Li

Jonathan H Huggins

2022/3/29

Challenges and opportunities in high dimensional variational inference

Akash Kumar Dhaka

Alejandro Catalina

Manushi Welandawe

Michael R Andersen

Jonathan Huggins

...

2021/12/6

The mutational signature comprehensive analysis toolkit (musicatk) for the discovery, prediction, and exploration of mutational signatures

Cancer research

Aaron Chevalier

Shiyi Yang

Zainab Khurshid

Nathan Sahelijo

Tong Tong

...

2021/12/1

Challenges for BBVI with Normalizing Flows

Akash Kumar Dhaka

Alejandro Catalina

Manushi Welandawe

Michael Riis Andersen

Jonathan H Huggins

...

2021/6/2

Bidirectional contact tracing could dramatically improve COVID-19 control

Nature communications

William J Bradshaw

Ethan C Alley

Jonathan H Huggins

Alun L Lloyd

Kevin M Esvelt

2021/1/11

The feasibility of targeted test-trace-isolate for the control of B. 1.1. 7 (preprint)

William Bradshaw

Jonathan Huggins

Alun Lloyd

Kevin Esvelt

2021

Independent versus truncated finite approximations for Bayesian nonparametric inference

Tin D Nguyen

Jonathan H Huggins

Lorenzo Masoero

Lester Mackey

Tamara Broderick

2020/12/9

Validated variational inference via practical posterior error bounds

Jonathan Huggins

Mikolaj Kasprzak

Trevor Campbell

Tamara Broderick

2020/6/3

Bidirectional contact tracing is required for reliable COVID-19 control (preprint)

William J Bradshaw

Ethan C Alley

Jonathan H Huggins

Alun L Lloyd

Kevin M Esvelt

2020

Robust, accurate stochastic optimization for variational inference

Advances in Neural Information Processing Systems

Akash Kumar Dhaka

Alejandro Catalina

Michael R Andersen

Måns Magnusson

Jonathan Huggins

...

2020

See List of Professors in Jonathan Huggins University(Boston University)

Co-Authors

H-index: 101
Jonathan P. How

Jonathan P. How

Massachusetts Institute of Technology

H-index: 70
Liam Paninski

Liam Paninski

Columbia University in the City of New York

H-index: 67
James Zou

James Zou

Stanford University

H-index: 56
Alun Lloyd

Alun Lloyd

North Carolina State University

H-index: 55
Aki Vehtari

Aki Vehtari

Aalto-yliopisto

H-index: 39
Daniel M. Roy

Daniel M. Roy

University of Toronto

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