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While diffusion models can successfully generate data and make predictions, they are predominantly designed for static images.
Physics-informed autoencoders for lyapunov-stable fluid flow prediction
N. Benjamin Erichson, Michael Muehlebach, and Michael W. Mahoney · 1905
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Scoring rules for continuous probability distributions
James E. Matheson and Robert L. Winkler · 1976
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Climate and wildfire in the western united states
Anthony L Westerling, Alexander Gershunov, Timothy J Brown, Daniel R Cayan, and Michael D Dettinger · 2003
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Weather forecasting with ensemble methods
Tilmann Gneiting and Adrian E. Raftery · 2005
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Statistical model for forecasting monthly large wildfire events in western united states
Haiganoush K Preisler and Anthony L Westerling · 2007
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300 billion served: Sources, perceptions, uses, and values of weather forecasts
Jeffrey K. Lazo, Rebecca E. Morss, and Julie L. Demuth · 2009
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Why should ensemble spread match the rmse of the ensemble mean?
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Probabilistic forecasting
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Deep unsupervised learning using nonequilibrium thermodynamics
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Deep learning for physical processes: Incorporating prior scientific knowledge
Emmanuel de Bézenac, Arthur Pajot, and Patrick Gallinari · 2018
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Neural networks for postprocessing ensemble weather forecasts
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S. Scher · 2018
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Yoo-Geun Ham, Jeong-Hwan Kim, and Jing-Jia Luo · 2019
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Generalization properties of feed-forward neural networks trained on lorenz systems
S. Scher and G. Messori · 2019
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Generative modeling by estimating gradients of the data distribution
Yang Song and Stefano Ermon · 2019
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Jonathan A. Weyn, Dale R. Durran, and Rich Caruana · 2019
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Deep spatial transformers for autoregressive data-driven forecasting of geophysical turbulence
Ashesh Chattopadhyay, Mustafa Mustafa, Pedram Hassanzadeh, and Karthik Kashinath · 2020
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Normalizing kalman filters for multivariate time series analysis
Emmanuel de Bézenac, Syama Sundar Rangapuram, Konstantinos Benidis, Michael Bohlke-Schneider, Richard Kurle, Lorenzo Stella, Hilaf Hasson, Patrick Gallinari, and Tim Januschowski · 2020
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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Physics-informed machine learning: case studies for weather and climate modelling
K. Kashinath, M. Mustafa, A. Albert, J-L. Wu, C. Jiang, S. Esmaeilzadeh, K. Azizzadenesheli, R. Wang, A. Chattopadhyay, A. Singh, A. Manepalli, D. Chirila, R. Yu, R. Walters, B. White, H. Xiao, H. A. Tchelepi, P. Marcus, A. Anandkumar, P. Hassanzadeh, and null Prabhat · 2020
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The united nations framework convention on climate change, the kyoto protocol, and the paris agreement: a summary
Jane A Leggett · 2020
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Learning stable models for prediction and control
Giorgos Mamakoukas, Ian Abraham, and Todd Murphey · 2020
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WeatherBench: A benchmark data set for data-driven weather forecasting
Stephan Rasp, Peter D. Dueben, Sebastian Scher, Jonathan A. Weyn, Soukayna Mouatadid, and Nils Thuerey · 2020
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Alvaro Sanchez-Gonzalez, Jonathan Godwin, Tobias Pfaff, Rex Ying, Jure Leskovec, and Peter W. Battaglia · 2020
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Score-based generative modeling through stochastic differential equations
Yang Song, Jascha Sohl-Dickstein, Diederik P Kingma, Abhishek Kumar, Stefano Ermon, and Ben Poole · 2020
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Long-range seasonal forecasting of 2m-temperature with machine learning
Etienne E Vos, Ashley Gritzman, Sibusisiwe Makhanya, Thabang Mashinini, and Campbell D Watson · 2020
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Towards physics-informed deep learning for turbulent flow prediction
Rui Wang, Karthik Kashinath, Mustafa Mustafa, Adrian Albert, and Rose Yu · 2020
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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, Weihua Hu, Alexander Merose, Stephan Hoyer, George Holland, Jacklynn Stott, Oriol Vinyals, Shakir Mohamed, and Peter Battaglia · 2022
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Jaideep Pathak, Shashank Subramanian, Peter Harrington, Sanjeev Raja, Ashesh Chattopadhyay, Morteza Mardani, Thorsten Kurth, David Hall, Zongyi Li, Kamyar Azizzadenesheli, Pedram Hassanzadeh, Karthik Kashinath, and Animashree Anandkumar · 2022
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Hierarchical text-conditional image generation with clip latents
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Data-driven medium-range weather prediction with a resnet pretrained on climate simulations: A new model for weatherbench
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Meta-learning dynamics forecasting using task inference
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