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.
44 episodios disponibles

Latest episodes of the podcast Earthly Machine Learning

Artificial Intelligence for Atmospheric Sciences: A Research Roadmap 11/01/2026
Differentiable and accelerated spherical harmonic and Wigner transforms 19/12/2025
Score-based diffusion nowcasting of GOES imagery 11/12/2025
FuXi-Ocean: A Global Ocean Forecasting System with Sub-Daily Resolution 04/12/2025
Beyond the Training Data: Confidence-Guided Mixing of Parameterizations in a Hybrid AI-Climate Model 28/11/2025
Climate in a Bottle: Towards a Generative Foundation Model for the Kilometer-Scale Global Atmosphere 23/11/2025
Probabilistic Measures for Fair AI and NWP Model Comparison 07/11/2025
Jigsaw: Training Multi-Billion-Parameter AI Weather Models With Optimized Model Parallelism 24/10/2025
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
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
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