Equivariant Machine Learning from Classical Physics

Explore a thought-provoking presentation on 'Equivariant ML from classical physics' delivered by Soledad Villar from John Hopkins University. Recorded during the weekly DataLearning working group meeting on November 22, 2022, this one-hour talk delves into the intersection of machine learning and classical physics. Gain insights into the development of new technologies based on Data Assimilation and Machine Learning from an interdisciplinary perspective. Discover how equivariant machine learning techniques can be applied to classical physics problems, potentially revolutionizing the field. Engage with cutting-edge research and expand your understanding of this innovative approach to data science and physics.

Data Learning: Equivariant ML from classical physics