Daniel Simpson

Daniel Simpson

University of Toronto

H-index: 36

North America-Canada

About Daniel Simpson

Daniel Simpson, With an exceptional h-index of 36 and a recent h-index of 32 (since 2020), a distinguished researcher at University of Toronto, specializes in the field of LLMs, Computational Statistics, Spatial Statistics, Bayesian Statistics, Numerical Linear Algebra.

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

Crossvalidatory model selection for Bayesian autoregressions with exogenous regressors

Thermodynamic AI and Thermodynamic Linear Algebra

Bayesian cross-validation by parallel Markov chain Monte Carlo

Thermodynamic Linear Algebra

The integrated nested laplace approximation for fitting dirichlet regression models

He, she, they: Using sex and gender in survey adjustment

Improving multilevel regression and poststratification with structured priors

Rank-normalization, folding, and localization: An improved R ̂ for assessing convergence of MCMC (with discussion)

Daniel Simpson Information

University

Position

___

Citations(all)

10313

Citations(since 2020)

8444

Cited By

4667

hIndex(all)

36

hIndex(since 2020)

32

i10Index(all)

54

i10Index(since 2020)

45

Email

University Profile Page

University of Toronto

Google Scholar

View Google Scholar Profile

Daniel Simpson Skills & Research Interests

LLMs

Computational Statistics

Spatial Statistics

Bayesian Statistics

Numerical Linear Algebra

Top articles of Daniel Simpson

Title

Journal

Author(s)

Publication Date

Crossvalidatory model selection for Bayesian autoregressions with exogenous regressors

arXiv preprint arXiv:2301.08276

Alex Cooper

Dan Simpson

Lauren Kennedy

Catherine Forbes

Aki Vehtari

2023/1/19

Thermodynamic AI and Thermodynamic Linear Algebra

Patrick J Coles

Maxwell Aifer

Kaelan Donatella

Denis Melanson

Max Hunter Gordon

...

2023/12/22

Bayesian cross-validation by parallel Markov chain Monte Carlo

arXiv preprint arXiv:2310.07002

Alex Cooper

Aki Vehtari

Catherine Forbes

Lauren Kennedy

Dan Simpson

2023/10/10

Thermodynamic Linear Algebra

arXiv preprint arXiv:2308.05660

Maxwell Aifer

Kaelan Donatella

Max Hunter Gordon

Thomas Ahle

Daniel Simpson

...

2023/8/10

The integrated nested laplace approximation for fitting dirichlet regression models

Journal of Computational and Graphical Statistics

Joaquín Martínez-Minaya

Finn Lindgren

Antonio López-Quílez

Daniel Simpson

David Conesa

2023/7/3

He, she, they: Using sex and gender in survey adjustment

arXiv

Lauren Kennedy

Katharine Khanna

Daniel Simpson

Andrew Gelman

Yajun Jia

...

2022/3/23

Improving multilevel regression and poststratification with structured priors

Bayesian Analysis

Yuxiang Gao

Lauren Kennedy

Daniel Simpson

Andrew Gelman

2021/9

Rank-normalization, folding, and localization: An improved R ̂ for assessing convergence of MCMC (with discussion)

Bayesian analysis

Aki Vehtari

Andrew Gelman

Daniel Simpson

Bob Carpenter

Paul-Christian Bürkner

2021/6

Treatment effect estimation with Multilevel Regression and Poststratification

arXiv preprint arXiv:2102.10003

Yuxiang Gao

Lauren Kennedy

Daniel Simpson

2021/2/19

Approximate Bayesian inference for latent Gaussian models in Stan

Journal of the Royal Statistical Society Series B: Statistical Methodology

Håvard Rue

Sara Martino

Nicolas Chopin

2009/4

Bayesian workflow

arXiv preprint arXiv:2011.01808

Andrew Gelman

Aki Vehtari

Daniel Simpson

Charles C Margossian

Bob Carpenter

...

2020/11/3

Using sex and gender in survey adjustment

arXiv preprint arXiv:2009.14401

Lauren Kennedy

Katharine Khanna

Daniel Simpson

Andrew Gelman

Yajun Jia

...

2020/9/30

Asynchronous gibbs sampling

Alexander Terenin

Daniel Simpson

David Draper

2020/6/3

LGM split sampler: An efficient MCMC sampling scheme for latent Gaussian models

Óli Páll Geirsson

Birgir Hrafnkelsson

Daniel Simpson

Helgi Sigurdarson

2020/5/1

Hamiltonian Monte Carlo using an adjoint-differentiated Laplace approximation: Bayesian inference for latent Gaussian models and beyond

Advances in Neural Information Processing Systems

Charles Margossian

Aki Vehtari

Daniel Simpson

Raj Agrawal

2020

See List of Professors in Daniel Simpson University(University of Toronto)

Co-Authors

H-index: 129
Andrew Gelman

Andrew Gelman

Columbia University in the City of New York

H-index: 78
Kerrie Mengersen

Kerrie Mengersen

Queensland University of Technology

H-index: 74
Mark Girolami

Mark Girolami

University of Cambridge

H-index: 63
Håvard Rue

Håvard Rue

King Abdullah University of Science and Technology

H-index: 55
Aki Vehtari

Aki Vehtari

Aalto-yliopisto

H-index: 24
Jo Eidsvik

Jo Eidsvik

Norges teknisk-naturvitenskaplige universitet

academic-engine