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5GraphCast: Learning skillful medium-range global weather forecasting
R. Lam, A. Sanchez-Gonzalez, M. Willson, P. Wirnsberger, M. Fortunato, F. Alet, S. Ravuri, T. Ewalds, Z. Eaton-Rosen, W. Hu and 8 other author(s). (2022)cite arxiv:2212.12794Comment: GraphCast code and trained weights are available at: https://github.com/deepmind/graphcast.
12 months ago by @annakrause
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idea:remoformer
deeplearning
climate
todo:read
weather
idea:remoformerdeeplearningclimatetodo:readweather
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2FengWu: Pushing the Skillful Global Medium-range Weather Forecast beyond 10 Days Lead
K. Chen, T. Han, J. Gong, L. Bai, F. Ling, J. Luo, X. Chen, L. Ma, T. Zhang, R. Su and 4 other author(s). (2023)cite arxiv:2304.02948Comment: 12 pages.
a year ago by @annakrause
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idea:remoformer
deeplearning
idea:big_data_geo_2
transformer
climate
todo:read
weather
idea:remoformerdeeplearningidea:big_data_geo_2transformerclimatetodo:readweather
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1Using Machine Learning to Parameterize Moist Convection: Potential for Modeling of Climate, Climate Change, and Extreme Events
P. O’Gorman, and J. Dwyer. Journal of Advances in Modeling Earth Systems, (2018)
a year ago by @annakrause
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deeplearning
climatemodeling
parametrizations
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deeplearningclimatemodelingparametrizationstodo:read
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1Stable machine-learning parameterization of subgrid processes for climate modeling at a range of resolutions
J. Yuval, and P. O’Gorman. Nature Communications, (2020)
a year ago by @annakrause
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parametrization
deeplearning
climate
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parametrizationdeeplearningclimatetodo:read
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2Adaptive Fourier Neural Operators: Efficient Token Mixers for Transformers
J. Guibas, M. Mardani, Z. Li, A. Tao, A. Anandkumar, and B. Catanzaro. (2021)cite arxiv:2111.13587.
a year ago by @annakrause
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deeplearningidea:big_data_geo_2transformerclimatefourieroperatortodo:read
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4FourCastNet: A Global Data-driven High-resolution Weather Model using Adaptive Fourier Neural Operators
J. Pathak, S. Subramanian, P. Harrington, S. Raja, A. Chattopadhyay, M. Mardani, T. Kurth, D. Hall, Z. Li, K. Azizzadenesheli and 3 other author(s). (February 2022)arXiv:2202.11214 physics.
a year ago by @annakrause
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idea:big_data_geo_2
prediction
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deeplearningidea:big_data_geo_2predictionclimatetodo:readweather
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2Solving Differential Equations Using Neural Network Solution Bundles
C. Flamant, P. Protopapas, and D. Sondak. (2020)cite arxiv:2006.14372Comment: 21 pages, 12 figures, 10 tables.
2 years ago by @annakrause
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3Long Short-Term Memory Recurrent Neural Network for Remaining Useful Life Prediction of Lithium-Ion Batteries
Y. Zhang, R. Xiong, H. He, and M. Pecht. IEEE Transactions on Vehicular Technology, 67 (7): 5695-5705 (July 2018)
3 years ago by @annakrause
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Lithium-ion-battery
deeplearning
Monte-Carlo-simulation
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Lithium-ion-batterydeeplearningMonte-Carlo-simulationtodo:read
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1A Bayesian-inspired, deep learning-based, semi-supervised domain adaptation technique for land cover mapping
B. Lucas, C. Pelletier, D. Schmidt, G. Webb, and F. Petitjean. Machine Learning, (Mar 4, 2021)
3 years ago by @annakrause
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landcover
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1A survey on concept drift adaptation
J. Gama, I. Zliobait\.e, A. Bifet, M. Pechenizkiy, and A. Bouchachia. ACM Computing Surveys, 46 (4): 1--37 (April 2014)
3 years ago by @annakrause
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7The Modern Mathematics of Deep Learning
J. Berner, P. Grohs, G. Kutyniok, and P. Petersen. (2021)cite arxiv:2105.04026Comment: This review paper will appear as a book chapter in the book "Theory of Deep Learning" by Cambridge University Press.
3 years ago by @annakrause
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basics
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3Open Graph Benchmark: Datasets for Machine Learning on Graphs
W. Hu, M. Fey, M. Zitnik, Y. Dong, H. Ren, B. Liu, M. Catasta, and J. Leskovec. (2020)cite arxiv:2005.00687Comment: Fix dataset bug in ogbg-code.
3 years ago by @annakrause
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3PDE-Net 2.0: Learning PDEs from Data with A Numeric-Symbolic Hybrid Deep Network
Z. Long, Y. Lu, and B. Dong. (2018)cite arxiv:1812.04426Comment: 16 pages, 15 figures. arXiv admin note: substantial text overlap with arXiv:1710.09668.
3 years ago by @annakrause
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PDEdeeplearningtodo:read
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1A Distributed Neural Network Architecture for Robust Non-Linear Spatio-Temporal Prediction
M. Karlbauer, S. Otte, H. Lensch, T. Scholten, V. Wulfmeyer, and M. Butz. (2019)cite arxiv:1912.11141Comment: 8 pages, 4 figures, video on https://www.youtube.com/watch?v=4VHhHYeWTzo.
3 years ago by @annakrause
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2Robust Low-Rank Discovery of Data-Driven Partial Differential Equations
J. Li, G. Sun, G. Zhao, and L. wei H. Lehman. Proceedings of the AAAI Conference on Artificial Intelligence, 34 (01): 767--774 (April 2020)
3 years ago by @annakrause
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PDE
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PDEtimeseriesdeeplearningclimatetodo:read
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2Deep Transformer Models for Time Series Forecasting: The Influenza Prevalence Case
N. Wu, B. Green, X. Ben, and S. O'Banion. (2020)cite arxiv:2001.08317Comment: 10 pages, 7 figures.
4 years ago by @annakrause
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2Weather and climate forecasting with neural networks: using general circulation models (GCMs) with different complexity as a study ground
S. Scher, and G. Messori. Geoscientific Model Development, 12 (7): 2797--2809 (2019)
4 years ago by @annakrause
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2Can Machines Learn to Predict Weather? Using Deep Learning to Predict Gridded 500-hPa Geopotential Height From Historical Weather Data
J. Weyn, D. Durran, and R. Caruana. Journal of Advances in Modeling Earth Systems, 11 (8): 2680-2693 (2019)
4 years ago by @annakrause
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1Generalization properties of feed-forward neural networks trained on Lorenz systems
S. Scher, and G. Messori. Nonlinear Processes in Geophysics, 26 (4): 381-399 (2019)
4 years ago by @annakrause
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1Challenges and design choices for global weather and climate models based on machine learning
P. Düben, and P. Bauer. Geoscientific Model Development, (October 2018)
4 years ago by @annakrause
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1The key challenge for machine learning parameterizations of clouds - Stephan Rasp

publications (hide)29
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5GraphCast: Learning skillful medium-range global weather forecasting

2FengWu: Pushing the Skillful Global Medium-range Weather Forecast beyond 10 Days Lead

1Using Machine Learning to Parameterize Moist Convection: Potential for Modeling of Climate, Climate Change, and Extreme Events

1Stable machine-learning parameterization of subgrid processes for climate modeling at a range of resolutions

2Adaptive Fourier Neural Operators: Efficient Token Mixers for Transformers

4FourCastNet: A Global Data-driven High-resolution Weather Model using Adaptive Fourier Neural Operators

2Solving Differential Equations Using Neural Network Solution Bundles

3Long Short-Term Memory Recurrent Neural Network for Remaining Useful Life Prediction of Lithium-Ion Batteries

1A Bayesian-inspired, deep learning-based, semi-supervised domain adaptation technique for land cover mapping

1A survey on concept drift adaptation

7The Modern Mathematics of Deep Learning

3Open Graph Benchmark: Datasets for Machine Learning on Graphs

3PDE-Net 2.0: Learning PDEs from Data with A Numeric-Symbolic Hybrid Deep Network

1A Distributed Neural Network Architecture for Robust Non-Linear Spatio-Temporal Prediction

2Robust Low-Rank Discovery of Data-Driven Partial Differential Equations

2Deep Transformer Models for Time Series Forecasting: The Influenza Prevalence Case

2Weather and climate forecasting with neural networks: using general circulation models (GCMs) with different complexity as a study ground

2Can Machines Learn to Predict Weather? Using Deep Learning to Predict Gridded 500-hPa Geopotential Height From Historical Weather Data

1Generalization properties of feed-forward neural networks trained on Lorenz systems

1Challenges and design choices for global weather and climate models based on machine learning

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