Foundation models for spatiotemporal systems
November 14, 2024 — November 14, 2024
dynamical systems
machine learning
neural nets
sciml
SDEs
signal processing
spatial
stochastic processes
time series
Suspiciously similar content
Foundation models for the whole planet, as opposed to classical NNs, as opposed to classical geospatial techniques.
1 Via modelling the governing equations
2 Incoming
IBM and NASA’s Prithvi project (Schmude et al. 2024)
3 References
Allen, Markou, Tebbutt, et al. 2025. “End-to-End Data-Driven Weather Prediction.”
Bodnar, Bruinsma, Lucic, et al. 2024. “Aurora: A Foundation Model of the Atmosphere.”
Chen, Kun, Bai, Ling, et al. 2024. “Towards an End-to-End Artificial Intelligence Driven Global Weather Forecasting System.”
Cheng, Min, Liu, et al. 2025. “TorchDA: A Python Package for Performing Data Assimilation with Deep Learning Forward and Transformation Functions.” Computer Physics Communications.
Chen, Kang, Han, Gong, et al. 2023. “FengWu: Pushing the Skillful Global Medium-Range Weather Forecast Beyond 10 Days Lead.”
Chen, Lei, Zhong, Zhang, et al. 2023. “FuXi: A Cascade Machine Learning Forecasting System for 15-Day Global Weather Forecast.” Npj Climate and Atmospheric Science.
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Grohs, and Herrmann. 2022. “Deep Neural Network Approximation for High-Dimensional Elliptic PDEs with Boundary Conditions.” IMA Journal of Numerical Analysis.
Guibas, Mardani, Li, et al. 2021. “Adaptive Fourier Neural Operators: Efficient Token Mixers for Transformers.”
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Huang, Gianinazzi, Yu, et al. 2024. “DiffDA: A Diffusion Model for Weather-Scale Data Assimilation.”
Keisler. 2022. “Forecasting Global Weather with Graph Neural Networks.”
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Lam, Sanchez-Gonzalez, Willson, et al. 2023a. “GraphCast: Learning Skillful Medium-Range Global Weather Forecasting.”
———, et al. 2023b. “Learning Skillful Medium-Range Global Weather Forecasting.” Science.
Mahesh, Collins, Bonev, et al. 2024. “Huge Ensembles Part I: Design of Ensemble Weather Forecasts Using Spherical Fourier Neural Operators.”
Manshausen, Cohen, Pathak, et al. 2024. “Generative Data Assimilation of Sparse Weather Station Observations at Kilometer Scales.”
McNally, Lessig, Lean, et al. 2024. “Data Driven Weather Forecasts Trained and Initialised Directly from Observations.”
Pathak, Subramanian, Harrington, et al. 2022. “Fourcastnet: A Global Data-Driven High-Resolution Weather Model Using Adaptive Fourier Neural Operators.”
Price, Sanchez-Gonzalez, Alet, et al. 2024. “GenCast: Diffusion-Based Ensemble Forecasting for Medium-Range Weather.”
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Schmude, Roy, Trojak, et al. 2024. “Prithvi WxC: Foundation Model for Weather and Climate.”
Willig, Zečević, Dhami, et al. 2022. “Can Foundation Models Talk Causality?”