Duncan Watson‐Parris

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All published works

Action	Title	Year	Authors
+ PDF Chat	Discovering Latent Structural Causal Models from Spatio-Temporal Data	2024	Kun Wang Sumanth Varambally Duncan Watson‐Parris Yi-An Ma Rong Yu
+ PDF Chat	Adapting While Learning: Grounding LLMs for Scientific Problems with Intelligent Tool Usage Adaptation	2024	Bohan Lyu Yadi Cao Duncan Watson‐Parris Leon Bergen Taylor Berg-Kirkpatrick Rong Yu
+ PDF Chat	Harnessing AI data-driven global weather models for climate attribution: An analysis of the 2017 Oroville Dam extreme atmospheric river	2024	Jorge Baño‐Medina Agniv Sengupta A. Michaelis Luca Delle Monache Julie Kalansky Duncan Watson‐Parris
+ PDF Chat	The impact of internal variability on benchmarking deep learning climate emulators	2024	Björn Lütjens Raffaele Ferrari Duncan Watson‐Parris Noelle E. Selin
+ PDF Chat	FaIRGP: A Bayesian Energy Balance Model for Surface Temperatures Emulation	2024	Shahine Bouabid Dino Sejdinović Duncan Watson‐Parris
+ PDF Chat	Multi-Fidelity Residual Neural Processes for Scalable Surrogate Modeling	2024	Ruijia Niu Dongxia Wu Kai Kim Yi-An Ma Duncan Watson‐Parris Rose Yu
+ PDF Chat	CloudTracks: A Dataset for Localizing Ship Tracks in Satellite Images of Clouds	2024	Muhammad Chaudhry Lyna Kim Jeremy Irvin Yuzu Ido Sonia Chu Jared Thomas Isobe Andrew Y. Ng Duncan Watson‐Parris
+ PDF Chat	FaIRGP: A Bayesian Energy Balance Model for Surface Temperatures Emulation	2023	Shahine Bouabid Dino Sejdinović Duncan Watson‐Parris
+ PDF Chat	Exploring Randomly Wired Neural Networks for Climate Model Emulation	2023	William Yik Sam J. Silva Andrew Geiss Duncan Watson‐Parris
+	Learning causal drivers of PyroCb	2023	Emiliano Díaz Gherardo Varando Fernando Iglesias‐Suarez Gustau Camps‐Valls Kenza Tazi Kara D. Lamb Duncan Watson‐Parris
+	FaIRGP: A Bayesian Energy Balance Model for Surface Temperatures Emulation	2023	Shahine Bouabid Dino Sejdinović Duncan Watson‐Parris
+	Physics-Informed Learning of Aerosol Microphysics	2022	Paula Harder Duncan Watson‐Parris Philip Stier Dominik Straßel Nicolas R. Gauger Janis Keuper
+	Identifying the Causes of Pyrocumulonimbus (PyroCb)	2022	Emiliano Díaz Salas-Porras Kenza Tazi Ashwin Braude Daniel Okoh Kara D. Lamb Duncan Watson‐Parris Paula Harder N. Meinert
+	Pyrocast: a Machine Learning Pipeline to Forecast Pyrocumulonimbus (PyroCb) Clouds	2022	Kenza Tazi Emiliano Díaz Salas-Porras Ashwin Braude Daniel Okoh Kara D. Lamb Duncan Watson‐Parris Paula Harder N. Meinert
+	Exploring Randomly Wired Neural Networks for Climate Model Emulation	2022	William Yik Sam J. Silva Andrew Geiss Duncan Watson‐Parris
+ PDF Chat	Physics-informed learning of aerosol microphysics	2022	Paula Harder Duncan Watson‐Parris Philip Stier Dominik Straßel Nicolas R. Gauger Janis Keuper
+	AODisaggregation: toward global aerosol vertical profiles	2022	Shahine Bouabid Duncan Watson‐Parris Sofija Stefanović Athanasios Nenes Dino Sejdinović
+ PDF Chat	Model calibration using ESEm v1.1.0 – an open, scalable Earth system emulator	2021	Duncan Watson‐Parris Andrew Williams Lucia Deaconu Philip Stier
+	Building high accuracy emulators for scientific simulations with deep neural architecture search	2021	Muhammad Kasim Duncan Watson‐Parris Lucia Deaconu Sophy Oliver Peter Hatfield D. H. Froula Giovanni Gregori M. J. Jarvis Samar Khatiwala Jun Korenaga
+	Using Non-Linear Causal Models to Study Aerosol-Cloud Interactions in the Southeast Pacific	2021	Andrew Jesson Peter Manshausen Alyson Douglas Duncan Watson‐Parris Yarin Gal Philip Stier
+	Model calibration using ESEm v1.0.0 – an open, scalable Earth System Emulator	2021	Duncan Watson‐Parris Andrew Williams Lucia Deaconu Philip Stier
+	Model calibration using ESEm v1.0.0 -- an open, scalable Earth System Emulator	2021	Duncan Watson‐Parris Andrew Williams Lucia Deaconu Philip Stier
+ PDF Chat	Machine learning for weather and climate are worlds apart	2021	Duncan Watson‐Parris
+	Supplementary material to &quot;Aerosol absorption in global models from AeroCom Phase III&quot;	2021	Maria Sand B. H. Samset Gunnar Myhre Jonas Gliß Susanne E. Bauer Huisheng Bian Mian Chin Ramiro Checa‐Garcia Paul Ginoux Zak Kipling
+ PDF Chat	RainBench: Towards Global Precipitation Forecasting from Satellite Imagery	2021	Christian Schroeder de Witt Catherine Tong Valentina Zantedeschi Daniele De Martini Freddie Kalaitzis Matthew Chantry Duncan Watson‐Parris Piotr Biliński
+	Emulating Aerosol Microphysics with Machine Learning	2021	Paula Harder Duncan Watson‐Parris Dominik Straßel Nicolas R. Gauger Philip Stier Janis Keuper
+	Using Non-Linear Causal Models to Study Aerosol-Cloud Interactions in the Southeast Pacific	2021	Andrew Jesson Peter Manshausen Alyson Douglas Duncan Watson‐Parris Yarin Gal Philip Stier
+	Up to two billion times acceleration of scientific simulations with deep neural architecture search	2020	Muhammad Kasim Duncan Watson‐Parris Lucia Deaconu Sophy Oliver Peter Hatfield D. H. Froula Giovanni Gregori M. J. Jarvis Samar Khatiwala Jun Korenaga
+	Building high accuracy emulators for scientific simulations with deep neural architecture search.	2020	Muhammad Kasim Duncan Watson‐Parris Lucia Deaconu Sophy Oliver Peter Hatfield D. H. Froula Giovanni Gregori M. J. Jarvis Samar Khatiwala Jun Korenaga
+	NightVision: Generating Nighttime Satellite Imagery from Infra-Red Observations	2020	Paula Harder William K. Jones Redouane Lguensat Shahine Bouabid James C. Fulton Dánell Quesada-Chacón Aris Marcolongo Sofija Stefanovic Yuhan Rao Peter Manshausen
+	RainBench: Towards Global Precipitation Forecasting from Satellite Imagery	2020	Christian Schroeder de Witt Catherine Tong Valentina Zantedeschi Daniele De Martini Freddie Kalaitzis Matthew Chantry Duncan Watson‐Parris Piotr Biliński
+	Cumulo: A Dataset for Learning Cloud Classes.	2019	Valentina Zantedeschi Fabrizio Falasca Alyson Douglas Richard C. Strange Matt J. Kusner Duncan Watson‐Parris
+	Detecting anthropogenic cloud perturbations with deep learning	2019	Duncan Watson‐Parris Samuel Sutherland Matthew W. Christensen Anthony L. Caterini Dino Sejdinović Philip Stier
+	Cumulo: A Dataset for Learning Cloud Classes	2019	Valentina Zantedeschi Fabrizio Falasca Alyson Douglas Richard C. Strange Matt J. Kusner Duncan Watson‐Parris
+ PDF Chat	Carrier localization mechanisms in In<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mrow><mml:msub><mml:mrow /><mml:mrow><mml:mi>x</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:math>Ga<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mrow><mml:msub><mml:mrow /><mml:mrow><mml:mn>1</mml:mn><mml:mo>−</mml:mo><mml:mi>x</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:math>N/GaN quantum wells	2011	Duncan Watson‐Parris M. J. Godfrey P. Dawson Rachel A. Oliver M. J. Galtrey M. J. Kappers C. J. Humphreys

Common Coauthors

Coauthor	Papers Together
Philip Stier	10
Paula Harder	6
Lucia Deaconu	6
Shahine Bouabid	5
Dino Sejdinović	5
Alyson Douglas	4
Valentina Zantedeschi	4
Janis Keuper	3
Samar Khatiwala	3
Muhammad Kasim	3
S. M. Vinko	3
J. Topp-Mugglestone	3
Peter Hatfield	3
M. J. Jarvis	3
E. Viezzer	3
Andrew Williams	3
Dominik Straßel	3
Peter Manshausen	3
Sophy Oliver	3
D. H. Froula	3
Kenza Tazi	3
Kara D. Lamb	3
Jun Korenaga	3
Giovanni Gregori	3
Nicolas R. Gauger	3
Ashwin Braude	2
N. Meinert	2
Matt J. Kusner	2
Emiliano Díaz Salas-Porras	2
Christian Schroeder de Witt	2
Daniele De Martini	2
Matthew Chantry	2
Fabrizio Falasca	2
Daniel Okoh	2
Andrew Jesson	2
Rong Yu	2
Richard C. Strange	2
Freddie Kalaitzis	2
Andrew Geiss	2
Sam J. Silva	2
Yarin Gal	2
Catherine Tong	2
William Yik	2
Yi-An Ma	2
Piotr Biliński	2
C. J. Humphreys	1
Maria Sand	1
M. J. Godfrey	1
Sofija Stefanovic	1
Taylor Berg-Kirkpatrick	1

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+	The frontier of simulation-based inference	2020	K. Cranmer Johann Brehmer Gilles Louppe	4
+ PDF Chat	Using Machine Learning to Parameterize Moist Convection: Potential for Modeling of Climate, Climate Change, and Extreme Events	2018	Paul A. O’Gorman J. G. Dwyer	4
+	Calibrate, emulate, sample	2020	Emmet Cleary Alfredo Garbuno-Iñigo Shiwei Lan Tapio Schneider Andrew M. Stuart	4
+ PDF Chat	Enforcing Analytic Constraints in Neural Networks Emulating Physical Systems	2021	Tom Beucler Michael S. Pritchard Stephan Rasp Jordan Ott Pierre Baldi Pierre Gentine	4
+	TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems	2016	Martı́n Abadi Ashish Agarwal Paul Barham Eugene Brevdo Zhifeng Chen Craig Citro Gregory S. Corrado Andy Davis Jay B. Dean Matthieu Devin	3
+	Combining data assimilation and machine learning to emulate a dynamical model from sparse and noisy observations: A case study with the Lorenz 96 model	2020	Julien Brajard Alberto Carrassi Marc Bocquet Laurent Bertino	3
+ PDF Chat	Constructing Summary Statistics for Approximate Bayesian Computation: Semi-Automatic Approximate Bayesian Computation	2012	Paul Fearnhead Dennis Prangle	3
+ PDF Chat	Deep learning to represent subgrid processes in climate models	2018	Stephan Rasp Michael S. Pritchard Pierre Gentine	3
+	Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning	2015	Yarin Gal Zoubin Ghahramani	3
+	Scikit-learn: Machine Learning in Python	2012	Fabián Pedregosa Gaël Varoquaux Alexandre Gramfort Vincent Michel Bertrand Thirion Olivier Grisel Mathieu Blondel Peter Prettenhofer Ron J. Weiss Vincent Dubourg	3
+	Mining gold from implicit models to improve likelihood-free inference	2020	Johann Brehmer Gilles Louppe Juan Pavez K. Cranmer	3
+ PDF Chat	Machine learning for weather and climate are worlds apart	2021	Duncan Watson‐Parris	2
+	Deep Gaussian Processes	2012	Andreas Damianou Neil D. Lawrence	2
+ PDF Chat	Thermal Equilibrium of the Atmosphere with a Given Distribution of Relative Humidity	1967	Syukuro Manabe R. T. Wetherald	2
+ PDF Chat	WeatherBench: A Benchmark Data Set for Data‐Driven Weather Forecasting	2020	Stephan Rasp Peter Dueben Sebastian Scher Jonathan A. Weyn Soukayna Mouatadid Nils Thuerey	2
+	Exact Gaussian Processes on a Million Data Points	2019	Ke Alexander Wang Geoff Pleiss Jacob R. Gardner Stephen Tyree Kilian Q. Weinberger Andrew Gordon Wilson	2
+ PDF Chat	Prognostic Validation of a Neural Network Unified Physics Parameterization	2018	Noah Brenowitz Christopher S. Bretherton	2
+	The fractional energy balance equation	2021	S. Lovejoy Roman Procyk Raphaël Hébert Lenin Del Rio Amador	2
+ PDF Chat	Coupled online learning as a way to tackle instabilities and biases in neural network parameterizations: general algorithms and Lorenz 96 case study (v1.0)	2020	Stephan Rasp	2
+	Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning	2015	Yarin Gal Zoubin Ghahramani	2
+ PDF Chat	Laboratory evidence of dynamo amplification of magnetic fields in a turbulent plasma	2018	Petros Tzeferacos A. Rigby A. F. A. Bott A. R. Bell R. Bingham A. Casner F. Cattaneo E. Churazov J. Emig Frederico Fiúza	1
+ PDF Chat	Consistent set of band parameters for the group-III nitrides AlN, GaN, and InN	2008	Patrick Rinke M. Winkelnkemper A. Qteish D. Bimberg Jörg Neugebauer Matthias Scheffler	1
+ PDF Chat	COSMIC EMULATION: FAST PREDICTIONS FOR THE GALAXY POWER SPECTRUM	2015	Juliana Kwan Katrin Heitmann Salman Habib Nikhil Padmanabhan Earl Lawrence Hal Finkel Nicholas Frontiere and Adrian Pope	1
+	CMA-ES for Hyperparameter Optimization of Deep Neural Networks	2016	Ilya Loshchilov Frank Hutter	1
+ PDF Chat	GALAXY CLUSTERING IN THE NEWFIRM MEDIUM BAND SURVEY: THE RELATIONSHIP BETWEEN STELLAR MASS AND DARK MATTER HALO MASS AT 1 <<i>z</i>< 2	2011	David A. Wake Katherine E. Whitaker Ivo Labbé Pieter van Dokkum Marijn Franx Ryan Quadri Gabriel Brammer Mariska Kriek Britt Lundgren Danilo Marchesini	1
+ PDF Chat	The galaxy–halo connection in the VIDEO survey at 0.5 <<i>z</i>< 1.7	2016	Peter Hatfield Sam Lindsay M. J. Jarvis Boris Häußler M. Vaccari A. Verma	1
+	Fully Convolutional Networks for Semantic Segmentation	2016	Evan Shelhamer Jonathan Long Trevor Darrell	1
+ PDF Chat	Long-Range Persistence in Global Surface Temperatures Explained by Linear Multibox Energy Balance Models	2017	Hege‐Beate Fredriksen Martin Rypdal	1
+	Hybrid Models with Deep and Invertible Features	2019	Eric Nalisnick Akihiro Matsukawa Yee Whye Teh Dilan Görür Balaji Lakshminarayanan	1
+	Stochastic Variational Video Prediction	2017	Mohammad Babaeizadeh Chelsea Finn Dumitru Erhan Roy H. Campbell Sergey Levine	1
+ PDF Chat	Deep Residual Learning for Image Recognition	2016	Kaiming He Xiangyu Zhang Shaoqing Ren Jian Sun	1
+ PDF Chat	Linear Latent Force Models Using Gaussian Processes	2013	Mauricio A. Álvarez David Luengo Neil D. Lawrence	1
+	Weakly- and Semi-Supervised Learning of a DCNN for Semantic Image Segmentation	2015	George Papandreou Liang-Chieh Chen Kevin Murphy Alan Yuille	1
+	Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs)	2015	Djork-Arné Clevert Thomas Unterthiner Sepp Hochreiter	1
+	Estimating Treatment Effects with Causal Forests: An Application	2019	Susan Athey Stefan Wager	1
+ PDF Chat	Free-carrier effects in gallium nitride epilayers: Valence-band dispersion	2001	Philip A. Shields R. J. Nicholas F. M. Peeters B. Beaumont P. Gibart	1
+ PDF Chat	Natural Evolution Strategies	2008	Daan Wierstra Tom Schaul Jan Peters Juergen Schmidhuber	1
+	Impact of Data Normalization on Deep Neural Network for Time Series Forecasting	2018	Samit Bhanja Abhishek Das	1
+	Hyperparameter Learning via Distributional Transfer	2018	Ho Chung Leon Law Peilin Zhao Junzhou Huang Dino Sejdinović	1
+ PDF Chat	Estimating Conditional Average Treatment Effects	2014	Jason Abrevaya Yu-Chin Hsu Robert P. Lieli	1
+ PDF Chat	Bayesian Interpolation	1992	David Mackay	1
+	Proceedings of the 25th international conference on Machine learning	2008	William W. Cohen Andrew McCallum Sam T. Roweis	1
+	Global space–time models for climate ensembles	2013	Stefano Castruccio Michael L. Stein	1
+	Rates of Convergence for Sparse Variational Gaussian Process Regression	2019	David R. Burt Carl Edward Rasmussen Mark van der Wilk	1
+	The Convergence Rate of Neural Networks for Learned Functions of Different Frequencies	2019	Ronen Basri David Jacobs Yoni Kasten Shira Kritchman	1
+	Combining crowd-sourcing and deep learning to explore the meso-scale organization of shallow convection	2019	Stephan Rasp Hauke Schulz Sandrine Bony Björn Stevens	1
+	Handbook of Approximate Bayesian Computation	2018		1
+ PDF Chat	Applying Machine Learning to Improve Simulations of a Chaotic Dynamical System Using Empirical Error Correction	2019	P.A. Watson	1
+	UNet++: A Nested U-Net Architecture for Medical Image Segmentation	2018	Zongwei Zhou Md Mahfuzur Rahman Siddiquee Nima Tajbakhsh Jianming Liang	1
+	GPyTorch: Blackbox Matrix-Matrix Gaussian Process Inference with GPU Acceleration	2018	Jacob R. Gardner Geoff Pleiss David Bindel Kilian Q. Weinberger Andrew Gordon Wilson	1