Archive Talks

A list of talks from previous years.

2021

• Joan Bruna - Deep Learning Barcelona: Geometric Deep Learning: Prospects and Challenges. 💻 Dec 22nd Video
• AGU - Dec 13th-17th 2021 Find the list of talks and posters by our team members in our latest newsletter. 📊 💻 🎆 Newsletter
• Laure Zanna - NeurIPS: Machine Learning and the Physical Sciences: The future of climate modeling in the age of machine learning (invited). 💻 🎆 Dec 13th More Info
• Judith Berner - ASP S2S Colloquium 2021: S2S predictability and uncertainty. 🎆 🌎 Dec 7th Video
• Joan Bruna - UW Data-driven methods in science and engineering seminar: Mathematical Prospects and Challenges of Machine Learning in the Physical World. 💻 🎆 Dec 3rd Video
• Laure Zanna - DOE AI4ESP workshop: AI for Oceans: Improving Climate Projections. 💻 🎆 Dec 1st Video
• Pierre Gentine - AI For Good: Better Better — machine learning for improved climate models and projections. 💻 🎆 Nov 17th Video
• Laure Zanna - AI For Good: Bridging observations and numerical modelling of the ocean using machine learning. 💻 🎆 Nov 10th Video
• Paul O' Gorman and Janni Yuval - AI for Good: Improving rainfall and water-cycle projections through machine learning. 💻 🎆 Nov 3rd Video
• Pierre Gentine - DOE AI4ESP workshop: Potential of Machine Learning for Climate Modeling. 💻 🎆 Nov 2nd Video
• Laure Zanna - Podcast “Climate Now”: Improving Climate Models with Machine Learning. 💻 🎆 Nov 2nd Listen
• KITP Conference: Machine Learning for Climate. Talks are available here . In particular:
  • Laure Zanna - Machine Learning for Ocean Closures: Advances and Lessons. 💻 🎆 Nov 1st Video
  • Alistair Adcroft - Towards using machine learning in real climate models. 💻 🌎 Nov 1st Video
• Paul O' Gorman - ESSICUMD: Changing Precipitation and the Potential for Machine Learning To Improve Climate Predictions. 💻 🎆 Oct 14th Video
• Pierre Gentine KGML 2021: Hybrid modeling (Physics + Machine Learning)to improve predictions of the hydrological cycle. 💻 🎆 Aug 13th Video
• Joan Bruna - MSRI Summer School, Mathematics of Deep Learning. 💻 Aug 5-7th Part 1 Part 2 Part 3 Part 4 Part 5
• Laure Zanna - One World Mathematics: Climate Modeling in the Age of Machine Learning. 💻 🎆 July 6th Video
• Joan Bruna - IPAM: Sparse Linear Programming and (simple) neural networks. 💻 Mar 4th Video
• Joan Bruna - Paris AI Research Institute: Mathematical aspects of neural network approximation and learning. 💻 Feb 11th Video
• Ryan Abernathey - ECMWF: Pangeo Forge. 📊 Feb 10th Video
• Ryan Abernathey - National Academies “Ocean Decade: U.S. Launch Meeting”: OceanCloud: Transforming oceanography with a new approach to data and computing. 📊 Feb 4th Video
• Laure Zanna - 2021 CESM Ocean Model: Discovering equations from data for ocean mesoscale parametrizations. 💻 🎆 Feb 3rd Video

2020

• Ryan Abernathey - JupyterCon 2020: Cloud Native Repositories for Big Scientific Data. 📊 Nov 3rd Video
• Marika Holland - CAMEE Research Seminar: Using Climate Models to predict changing Arctic sea ice. 🎆 🌎 Oct 23rd Video
• Laure Zanna - IMSI: Blending Physics and Machine Learning for Climate Projections. 💻 🎆 Oct 9th Video
• Pierre Gentine - AI4ESS Summer School: Physics-guided Machine Learning. 💻 🎆 Jun 26th Video
• Marika Holland - M6 L5: Climate Modeling to Understand a Changing Arctic. 🎆 🌎 Mar 17th Video

2019

• Marika Holland - IASC Medal 2019: Perspectives on Predicting Arctic Sea Ice From Seasons to Centuries. 🎆 🌎 May 31st Video
• Julie Deshayes - Museum national d’Histoire naturelle The Oceanic Change (in French). 🎆 🌎 May 22nd Video
• Alistair Adcroft - 2019 SIAM conference: Challenges in modelling the oceans for climate. 🎆 🌎 Feb Video