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About the Atmosphere/ML Workshop 2026 category
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0
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41
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4 March 2026
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Andrew Ooi: Neural Ordinary Differencial EquationsDEs training session
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1
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111
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20 August 2026
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Welcome to the Connecting Machine Learning to Earth System Science Workshop!
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1
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43
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19 August 2026
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Wei Ji Leong: CuPy-Xarray: towards direct to GPU decoding of raster file formats
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1
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62
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18 August 2026
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Tennessee Leeuwenburg: Auto-encoder training sessions
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1
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234
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16 August 2026
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Steve Sherwood: Breakout: Physics-informed / Hybrid Machine Learning
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0
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70
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12 August 2026
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Yue Sun, Micael Oliveira, Edward Yang, Taimoor Sohail & Sanaa Hobeichi: GenAI breakout session
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0
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89
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12 August 2026
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Terry O'Kane: Novel neural operator and transformer architectures for climate prediction
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0
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85
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3 August 2026
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Andrew Zammit Mangion: Physics-based machine learning models for spatio-temporal forecasting
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0
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60
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16 July 2026
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William Edge: Gaussian Process Regression for multi-scale oceanographic observations
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0
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27
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21 July 2026
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Zhihao Deng*: Climatological Anomalies Projection using Neural Ordinary Differential Equations
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0
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33
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21 July 2026
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Jasmine Peterson*: Machine Learning and Australia’s shape
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0
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29
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21 July 2026
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Haoran Li, Shixue Li: Coarse-to-Fine: Multi-source Fusion for Bias-Corrected Precipitation Downscaling
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0
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22
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21 July 2026
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Ryan Holmes: Coastal downscaling of Australian seasonal sea level and sea surface temperature forecasts using neural networks
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0
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23
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21 July 2026
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Lynn Zhou: Rapid Forecast‑Based Attribution via a Climate Emulator
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0
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23
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21 July 2026
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Pearse Buchanan: Optimization of Australia's ocean biogeochemical model with a machine learning surrogate
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0
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23
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21 July 2026
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Abhnil Amtesh Prasad: WRF-LES training data generation framework for AI surrogates of parameterized convection
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0
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22
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21 July 2026
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Chandana Nagenahally Manjunath*: Dynamic Network Analysis of ENSO-driven Global Commodity Price Volatility: Implications for Food and Energy Security
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0
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27
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21 July 2026
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Ulrich Engelke, Dirk Slawinski and Tisham Dhar: Designing AI for Earth Science
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0
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21
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20 July 2026
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Krish Singh: Using Machine learning to calibrate complex process-based models for carbon stock projection in NSW forests
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0
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13
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20 July 2026
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Jakob Gradl: A hybrid variational physics informed/physics encoded neural network for strictly mass-conserving joint inversion of mass and momentum balance in ice flow modelling
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0
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18
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20 July 2026
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Peter Oke: When Machine Learning Breaks the Ocean: Why Dynamics Still Matter
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0
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27
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20 July 2026
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Nayan Meghsham Talmale: CMIP6 Fidelity in Capturing the Variability of Compound Events
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0
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13
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20 July 2026
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Li Wang: AI-Assisted Porting and Performance Optimization of LFRic Kernels
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0
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16
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20 July 2026
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Irina Rudeva: When Observations Are Sparse: Shared Reanalysis Biases in Southern Ocean MSLP and Insights from Machine Learning
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0
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24
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20 July 2026
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Tishampati Dhar: A review of Geospatial Foundation models, Embeddings and Practical Applications
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0
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21
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20 July 2026
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Christian Stassen: Machine learning for regional climate downscaling in the Australian Climate Service
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0
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29
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20 July 2026
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Taimoor Sohail: Towards a Machine Learning Ocean Emulation Framework for Decadal Climate Prediction
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0
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24
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20 July 2026
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Kevin Horner, Daimon Byl & Benjamin Cottrell: Practical Gray-Box Universal Differential Equation Methods for Chaotic Climate-Relevant Dynamics
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0
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21
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20 July 2026
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Spencer Patrick Clark: Pattern scaling in an overshoot world
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0
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17
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20 July 2026
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