Lawrence Berkeley National Laboratory

Understanding the role of symmetry in the physical sciences is critical for choosing an appropriate machine-learning method. While invariant models are the most prevalent symmetry-aware models, equivariant models such as Euclidean neural networks more faithfully represent physical interactions and are ready to take on challenges across the physical sciences.