An acausal modeling framework for automatically parallelized scientific machine learning (SciML) in Julia. A computer algebra system for integrated symbolics for physics-informed machine learning and automated transformations of differential equations
Also throws a better error for the case where a differential is not caught in the initialization system handling. Fixes https://github.com/SciML/ModelingToolkit.jl/issues/3029