Daniel Williamson

Daniel Williamson

University of Exeter

H-index: 19

Europe-United Kingdom

About Daniel Williamson

Daniel Williamson, With an exceptional h-index of 19 and a recent h-index of 17 (since 2020), a distinguished researcher at University of Exeter, specializes in the field of Statistics, Uncertainty Quantification, Climate model tuning, Bayesian methods.

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

Coexchangeable process modelling for uncertainty quantification in joint climate reconstruction

Iron and risk of dementia: Mendelian randomisation analysis in UK Biobank

Feature calibration for computer models

Engaging publics in the transition to smart mobilities

On the meaning of uncertainty for ethical AI: philosophy and practice

De‐Tuning Albedo Parameters in a Coupled Climate Ice Sheet Model to Simulate the North American Ice Sheet at the Last Glacial Maximum

Toward machine-assisted tuning avoiding the underestimation of uncertainty in climate change projections

Deep gaussian process emulation using stochastic imputation

Daniel Williamson Information

University

Position

___

Citations(all)

1556

Citations(since 2020)

1196

Cited By

827

hIndex(all)

19

hIndex(since 2020)

17

i10Index(all)

27

i10Index(since 2020)

24

Email

University Profile Page

Google Scholar

Daniel Williamson Skills & Research Interests

Statistics

Uncertainty Quantification

Climate model tuning

Bayesian methods

Top articles of Daniel Williamson

Coexchangeable process modelling for uncertainty quantification in joint climate reconstruction

Journal of the American Statistical Association

2024/3/1

Iron and risk of dementia: Mendelian randomisation analysis in UK Biobank

Journal of Medical Genetics

2024/1/8

Feature calibration for computer models

arXiv preprint arXiv:2310.18875

2023/10/29

Engaging publics in the transition to smart mobilities

GeoJournal

2023/10

On the meaning of uncertainty for ethical AI: philosophy and practice

arXiv preprint arXiv:2309.05529

2023/9/11

Daniel Williamson
Daniel Williamson

H-Index: 13

Sabina Leonelli
Sabina Leonelli

H-Index: 29

De‐Tuning Albedo Parameters in a Coupled Climate Ice Sheet Model to Simulate the North American Ice Sheet at the Last Glacial Maximum

Journal of Geophysical Research: Earth Surface

2023/8

Niall Gandy
Niall Gandy

H-Index: 4

Daniel Williamson
Daniel Williamson

H-Index: 13

Toward machine-assisted tuning avoiding the underestimation of uncertainty in climate change projections

Science Advances

2023/7/19

Daniel Williamson
Daniel Williamson

H-Index: 13

Deep gaussian process emulation using stochastic imputation

Technometrics

2023/4/3

Daniel Williamson
Daniel Williamson

H-Index: 13

Serge Guillas
Serge Guillas

H-Index: 14

A review of planting principles to identify the right place for the right tree for ‘net zero plus’ woodlands: Applying a place‐based natural capital framework for sustainable …

2023/4

‘I feel the weather and you just know’. Narrating the dynamics of commuter mobility choices

Journal of Transport Geography

2022/7/1

Daniel Williamson
Daniel Williamson

H-Index: 13

Quantifying spatio-temporal boundary condition uncertainty for the North American deglaciation

SIAM/ASA Journal on Uncertainty Quantification

2022/6/30

Quantifying uncertainties in global monthly mean sea surface temperature and sea ice at the Last Glacial Maximum

EGU General Assembly Conference Abstracts

2022/5

Emulation of high-resolution land surface models using sparse Gaussian processes with application to JULES

Geoscientific Model Development

2022/3/8

Evan Baker
Evan Baker

H-Index: 2

Daniel Williamson
Daniel Williamson

H-Index: 13

Challenges in calibrating a large-scale stochastic meta-population model of COVID-19 in England and Wales

2022/2/10

Tuning and quantifying parametric uncertainty of climate change simulations, 16

2022

Daniel Williamson
Daniel Williamson

H-Index: 13

Cross-Validation--based Adaptive Sampling for Gaussian Process Models

SIAM/ASA Journal on Uncertainty Quantification

2022

Efficient calibration for high-dimensional computer model output using basis methods

International Journal for Uncertainty Quantification

2022

Frédéric Hourdin, Brady Ferster, 2 Julie Deshayes, 2 Juliette Mignot, 2 Ionela Musat

2022/12/3

Daniel Williamson
Daniel Williamson

H-Index: 13

Process-based climate model development harnessing machine learning: III. The Representation of Cumulus Geometry and their 3D Radiative Effects

Authorea Preprints

2022/11/24

Modeling the GABLS4 strongly-stable boundary layer with a GCM parameterization: parametric sensitivity or intrinsic limits?

Authorea Preprints

2022/11/21

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