Recorded 27 October 2022. Soledad Villar of Johns Hopkins University presents "Introduction to equivariant machine learning" at IPAM's Mathematical Advances for Multi-Dimensional Microscopy Workshop. Abstract: Equivariant machine learning refers to machine learning models that respect the fundamental symmetries of physical descriptions. In this talk we will introduce the fundamentals of equivariant machine learning and explain how these models can be implemented. Learn more online at: http://www.ipam.ucla.edu/programs/workshops/workshop-ii-mathematical-advances-for-multi-dimensional-microscopy/?tab=schedule