Earthly Machine Learning

Por: Amirpasha
“Earthly Machine Learning (EML)” offers AI-generated insights into cutting-edge machine learning research in weather and climate sciences. Powered by Google NotebookLM, each episode distils the essence of a standout paper, helping you decide if it’s worth a deeper look. Stay updated on the ML innovations shaping our understanding of Earth.
It may contain hallucinations.
37 episodios disponibles

Latest episodes of the podcast Earthly Machine Learning

XiChen: An observation-scalable fully AI-driven global weather forecasting system with 4D variational knowledge 18/10/2025
FuXi Weather : A data-to-forecast machine learning system for global weather 03/10/2025
Probabilistic Emulation of a Global Climate Model with Spherical DYffusion 25/09/2025
FourCastNet 3: A geometric approach to probabilistic machine-learning weather forecasting at scale 16/09/2025
Can AI weather models predict out-of-distribution gray swan tropical cyclones? 16/08/2025
Probabilistic Emulation of a Global Climate Model with Spherical DYffusion 09/08/2025
Do AI models produce better weather forecasts than physics-based models? A quantitative evaluation case study of Storm Ciarán 03/08/2025
Early Warning of Complex Climate Risk with Integrated Artificial Intelligence 04/07/2025
On Some Limitations of Current Machine Learning Weather Prediction Models 27/06/2025
Artificial intelligence for modeling and understanding extreme weather and climate events 15/06/2025
Fixing the Double Penalty in Data-Driven Weather Forecasting Through a Modified Spherical Harmonic Loss Function 08/06/2025
Climate-invariant machine learning 09/05/2025
ClimaX: A foundation model for weather and climate 02/05/2025
AI-empowered Next-Generation Multiscale Climate Modelling for Mitigation and Adaptation 25/04/2025
FourCastNet – Accelerating Global High-Resolution Weather Forecasting Using Adaptive Fourier Neural Operators 18/04/2025
Knowledge-guided machine learning can improve carbon cycle quantification in agroecosystems 11/04/2025
AtmoRep: A stochastic model of atmosphere dynamics using large scale representation learning 04/04/2025
Finding the Right XAI Method—A Guide for the Evaluation and Ranking of Explainable AI Methods in Climate Science 27/03/2025
Pangu-Weather — Accurate medium-range global weather forecasting with 3D neural networks 21/03/2025
GRAPHDOP — Towards Skillful Data-Driven Medium-Range Weather Forecasts 14/03/2025
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