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 ...

OWATONNA, Minn. — At about 10:30 in the morning on Feb. 15. 1974, Mary K. Schlais left her home in Minneapolis, planning to hitchhike to an art show in Chicago. Later that day in 1974, according ...

py-pde is a Python package for solving partial differential equations (PDEs). The package provides classes for grids on which scalar and tensor fields can be defined. The associated differential ...

The development and analysis of algorithms for approximating solutions to mathematical problems. Topics covered include: approximating functions, finding roots, approximating derivatives and integrals ...

As an example, a method is proposed for “parallelizing” the numerical integration of an ordinary differential equation, which process, by all standard methods, is entirely serial.