3 papers
math.NA2026
Discovering PDEs equivariant under rigid motions
Francesco Ballerin, Erlend Grong
We consider the problem of PDE discovery from possibly noisy observations under the hypothesis that the underlying dynamic is symmetric in all rigid motions. Rather than using a ge…
math.AP2026
Equivariant nonlinear partial differential operators on constant curvature spaces
Francesco Ballerin, Erlend Grong
Motivated by PDE-learning, we give a classifying space for nonlinear partial differential operators equivariant under the action of isometries. This classifying space is for operat…
cs.LG2025
SO(3)-Equivariant Neural Networks for Learning from Scalar and Vector Fields on Spheres
Francesco Ballerin, Nello Blaser, Erlend Grong
Analyzing scalar and vector fields on the sphere, such as temperature or wind speed and direction on Earth, is a difficult task. Models should respect both the rotational symmetrie…