Fetching the paper…
Reading the bibliography…
Machine learning (ML)-based weather models have recently undergone rapid improvements.
Gaussian processes for machine learning , volume 2
Christopher KI Williams and Carl Edward Rasmussen · 2006
Earlier work this paper cites.
The shuttle radar topography mission
Tom G Farr, Paul A Rosen, Edward Caro, Robert Crippen, Riley Duren, Scott Hensley, Michael Kobrick, Mimi Paller, Ernesto Rodriguez, Ladislav Roth, et al · 2007
Earlier work this paper cites.
Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2014
Earlier work this paper cites.
Value: A framework to validate downscaling approaches for climate change studies
Douglas Maraun, Martin Widmann, José M Gutiérrez, Sven Kotlarski, Richard E Chandler, Elke Hertig, Joanna Wibig, Radan Huth, and Renate AI Wilcke · 2015
Earlier work this paper cites.
U-net: Convolutional networks for biomedical image segmentation
Olaf Ronneberger, Philipp Fischer, and Thomas Brox · 2015
Earlier work this paper cites.
Deep learning
Yann LeCun, Yoshua Bengio, and Geoffrey Hinton · 2015
Earlier work this paper cites.
Film: Visual reasoning with a general conditioning layer
Ethan Perez, Florian Strub, Harm De Vries, Vincent Dumoulin, and Aaron Courville · 2018
Earlier work this paper cites.
Convolutional conditional neural processes
Jonathan Gordon, Wessel P Bruinsma, Andrew YK Foong, James Requeima, Yann Dubois, and Richard E Turner · 2019
Cited alongside, same era.
The era5 global reanalysis
Hans Hersbach, Bill Bell, Paul Berrisford, Shoji Hirahara, András Horányi, Joaquín Muñoz-Sabater, Julien Nicolas, Carole Peubey, Raluca Radu, Dinand Schepers, et al · 2020
Cited alongside, same era.
Graphcast: Learning skillful medium-range global weather forecasting
Remi Lam, Alvaro Sanchez-Gonzalez, Matthew Willson, Peter Wirnsberger, Meire Fortunato, Alexander Pritzel, Suman Ravuri, Timo Ewalds, Ferran Alet, Zach Eaton-Rosen, et al · 2022
Cited alongside, same era.
Jaideep Pathak, Shashank Subramanian, Peter Harrington, Sanjeev Raja, Ashesh Chattopadhyay, Morteza Mardani, Thorsten Kurth, David Hall, Zongyi Li, Kamyar Azizzadenesheli, et al · 2022
Cited alongside, same era.
Convolutional conditional neural processes for local climate downscaling
Anna Vaughan, Will Tebbutt, J Scott Hosking, and Richard E Turner · 2022
Fengwu: Pushing the skillful global medium-range weather forecast beyond 10 days lead
Kang Chen, Tao Han, Junchao Gong, Lei Bai, Fenghua Ling, Jing-Jia Luo, Xi Chen, Leiming Ma, Tianning Zhang, Rui Su, et al · 2023
Closest in time.
Accurate medium-range global weather forecasting with 3d neural networks
Kaifeng Bi, Lingxi Xie, Hengheng Zhang, Xin Chen, Xiaotao Gu, and Qi Tian · 2023
Closest in time.
Deep learning for day forecasts from sparse observations
Marcin Andrychowicz, Lasse Espeholt, Di Li, Samier Merchant, Alex Merose, Fred Zyda, Shreya Agrawal, and Nal Kalchbrenner · 2023
Closest in time.
Active learning with convolutional gaussian neural processes for environmental sensor placement
Tom R Andersson, Wessel P Bruinsma, Stratis Markou, Daniel C Jones, J Scott Hosking, James Requeima, Alejandro Coca-Castro, Anna Vaughan, Anna-Louise Ellis, Matthew Lazzara, et al · 2023
Closest in time.
Aktuelle stündliche stationsmessungen der lufttemperatur und luftfeuchte für deutschland., 2023
Wetterdienst · 2023
Closest in time.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Towards multi-spatiotemporal-scale generalized pde modeling
Jayesh K Gupta and Johannes Brandstetter · 2022
Cited alongside, same era.
Climax: A foundation model for weather and climate
Tung Nguyen, Johannes Brandstetter, Ashish Kapoor, Jayesh K Gupta, and Aditya Grover · 2023
Cited alongside, same era.
DeepSensor: A Python package for modelling environmental data with convolutional neural processes, July 2023
Tom Robin Andersson · 2023
Closest in time.
Neuralprocesses. A framework for composing Neural Processes in Python., July 2023
Wessel Bruinsma · 2023
Closest in time.