The ocean is inherently chaotic, yet existing data-driven ocean models produce deterministic forecasts. In our new preprint, we introduce Njord, a probabilistic graph neural network for ensemble ocean forecasting. Link: arxiv.org/abs/2605.15470 A couple highlights below 🧵

Are you interested in ML for space/plasma physics? I'll be presenting “Graph-based Neural Space Weather Forecasting” this Saturday at the ML for physics workshop in San Diego @neuripsconf.bsky.social 🚀 📄 Paper: arxiv.org/abs/2509.19605 💻 Code: github.com/fmihpc/space... #AI4Science #ML4PS

I am recruiting PhD students for 2026!😃 You want to reveal the geometric signatures of natural and artificial intelligence, and understand computations in brains and AI? 🌐🧠🤖 Apply to the UCSB Geometric Intelligence Lab ✨ This is the view you'd have from... your desk🌴

ECMWF with two new papers right before christmas. AIFS-CRPS: arxiv.org/abs/2412.158... GraphDOP (the first truly end2end global weather model): arxiv.org/abs/2412.15687 Here they are added to the SotA tracker: docs.google.com/spreadsheets...

🧵 Today with @polymathicai.bsky.social and others we're releasing two massive datasets that span dozens of fields - from bacterial growth to supernova! We want this to enable multi-disciplinary foundation model research.

1/ 🚀 New Paper Alert: Spotlight at NeurIPS ML and the Physical Sciences Workshop! We explore the intersection of high-energy physics and machine learning. What's the challenge we’re targeting, and why does it matter? Let's dive in! 🧵👇 🚀 #AI #MachineLearning #Physics #ML4PS #NeurIPS #AcademicSky

🌊 Ocean currents around Antarctica from our high-resolution (3 km) ocean model. 🧪 #FESOM #SciArt

🌊 Meet SeaCast, a new, openly available graph neural network for regional ocean forecasting. Paper: arxiv.org/abs/2410.11807. Looking forward to presenting this work at the Climate Change AI workshop taking place at @neuripsconf.bsky.social in December! 🧵 Small thread below.