Physicists model the world around us by starting from fundamental principles like symmetries and conservation laws. Some soft and biophysical systems may lift these foundational rules, producing complex behavior that is hard to understand without new approaches to model-building. To address this challenge, we combine physical theory and machine learning in order to guide scientific discovery for a range of physical and biological experiments.
