Richard E Turner

Richard E Turner

University of Cambridge

H-index: 49

Europe-United Kingdom

About Richard E Turner

Richard E Turner, With an exceptional h-index of 49 and a recent h-index of 45 (since 2020), a distinguished researcher at University of Cambridge, specializes in the field of machine learning, Bayesian inference, probabilistic modelling.

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

SportsNGEN: Sustained Generation of Multi-player Sports Gameplay

A Generative Model of Symmetry Transformations

Identifiable Feature Learning for Spatial Data with Nonlinear ICA

Denoising Diffusion Probabilistic Models in Six Simple Steps

Guided Autoregressive Diffusion Models with Applications to PDE Simulation

Optimising Distributions with Natural Gradient Surrogates

Can We Remove the Square-Root in Adaptive Gradient Methods? A Second-Order Perspective

Kronecker-Factored Approximate Curvature for modern neural network architectures

Richard E Turner Information

University

Position

Professor

Citations(all)

9559

Citations(since 2020)

7753

Cited By

4414

hIndex(all)

49

hIndex(since 2020)

45

i10Index(all)

106

i10Index(since 2020)

92

Email

University Profile Page

University of Cambridge

Google Scholar

View Google Scholar Profile

Richard E Turner Skills & Research Interests

machine learning

Bayesian inference

probabilistic modelling

Top articles of Richard E Turner

Title

Journal

Author(s)

Publication Date

SportsNGEN: Sustained Generation of Multi-player Sports Gameplay

arXiv preprint arXiv:2403.12977

Lachlan Thorpe

Lewis Bawden

Karanjot Vendal

John Bronskill

Richard E Turner

2024/2/10

A Generative Model of Symmetry Transformations

arXiv preprint arXiv:2403.01946

James Urquhart Allingham

Bruno Kacper Mlodozeniec

Shreyas Padhy

Javier Antorán

David Krueger

...

2024/3/4

Identifiable Feature Learning for Spatial Data with Nonlinear ICA

Hermanni Hälvä

Jonathan So

Richard E Turner

Aapo Hyvärinen

2024/4/18

Denoising Diffusion Probabilistic Models in Six Simple Steps

arXiv preprint arXiv:2402.04384

Richard E Turner

Cristiana-Diana Diaconu

Stratis Markou

Aliaksandra Shysheya

Andrew YK Foong

...

2024/2/6

Guided Autoregressive Diffusion Models with Applications to PDE Simulation

Federico Bergamin

Cristiana Diaconu

Aliaksandra Shysheya

Paris Perdikaris

José Miguel Hernández-Lobato

...

2024/3/3

Optimising Distributions with Natural Gradient Surrogates

Jonathan So

Richard E Turner

2024/4/18

Can We Remove the Square-Root in Adaptive Gradient Methods? A Second-Order Perspective

arXiv preprint arXiv:2402.03496

Wu Lin

Felix Dangel

Runa Eschenhagen

Juhan Bae

Richard E Turner

...

2024/2/5

Kronecker-Factored Approximate Curvature for modern neural network architectures

Advances in Neural Information Processing Systems

Runa Eschenhagen

Alexander Immer

Richard Turner

Frank Schneider

Philipp Hennig

2024/2/13

Aardvark Weather: end-to-end data-driven weather forecasting

arXiv preprint arXiv:2404.00411

Anna Vaughan

Stratis Markou

Will Tebbutt

James Requeima

Wessel P Bruinsma

...

2024/3/30

Transformer Neural Autoregressive Flows

arXiv preprint arXiv:2401.01855

Massimiliano Patacchiola

Aliaksandra Shysheya

Katja Hofmann

Richard E Turner

2024/1/3

Pde-refiner: Achieving accurate long rollouts with neural pde solvers

Advances in Neural Information Processing Systems

Phillip Lippe

Bas Veeling

Paris Perdikaris

Richard Turner

Johannes Brandstetter

2024/2/13

Spatially-Coherent Probabilistic Downscaling of Daily Precipitation in Ungauged Mountain Locations: a Transfer Learning Study in the Swiss Alps and the Langtang Valley, Nepal.

Marc Girona-Mata

Andrew Orr

Richard E Turner

2024/3/7

Lifelong Learning for Deep Neural Networks with Bayesian Principles

Cuong V Nguyen

Siddharth Swaroop

Thang D Bui

Yingzhen Li

Richard E Turner

2024

Geometric neural diffusion processes

Advances in Neural Information Processing Systems

Emile Mathieu

Vincent Dutordoir

Michael Hutchinson

Valentin De Bortoli

Yee Whye Teh

...

2024/2/13

Pushing the Limits of Subseasonal-to-Seasonal Sea Ice Forecasting with Deep Generative Modelling

Andrew McDonald

Jonathan Smith

Peter Yatsyshin

Tom Andersson

Ellen Bowler

...

2024/3/7

An introduction to transformers

arXiv preprint arXiv:2304.10557

Richard E Turner

2023/4/20

Sim2real for environmental neural processes

arXiv preprint arXiv:2310.19932

Jonas Scholz

Tom R Andersson

Anna Vaughan

James Requeima

Richard E Turner

2023/10/30

Environmental sensor placement with convolutional Gaussian neural processes

Environmental Data Science

Tom R Andersson

Wessel P Bruinsma

Stratis Markou

James Requeima

Alejandro Coca-Castro

...

2023/1

Structured Inverse-Free Natural Gradient: Memory-Efficient & Numerically-Stable KFAC for Large Neural Nets

arXiv preprint arXiv:2312.05705

Wu Lin

Felix Dangel

Runa Eschenhagen

Kirill Neklyudov

Agustinus Kristiadi

...

2023/12/9

Autoregressive conditional neural processes

International Conference on Learning Representations (ICLR), 11th

Wessel P Bruinsma

Stratis Markou

James Requiema

Andrew YK Foong

Tom R Andersson

...

2023/3/25

See List of Professors in Richard E Turner University(University of Cambridge)

Co-Authors

H-index: 124
Zoubin Ghahramani

Zoubin Ghahramani

University of Cambridge

H-index: 66
Roy D. Patterson

Roy D. Patterson

University of Cambridge

H-index: 53
Maneesh Sahani

Maneesh Sahani

University College London

H-index: 50
José Miguel Hernández-Lobato

José Miguel Hernández-Lobato

University of Cambridge

H-index: 25
Daniel Hernández-Lobato

Daniel Hernández-Lobato

Universidad Autónoma de Madrid

H-index: 19
Yingzhen Li

Yingzhen Li

Imperial College London

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