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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 a…
Distributed High-Performance Symbolic Regression in Julia
Optimize Julia Functions With MLIR and XLA for High-Performance Execution on CPU, GPU, TPU and more.
Almost trivial distributed parallelization of stencil-based GPU and CPU applications on a regular staggered grid
Fast, general-purpose interactive applications for complex systems
Basic functionality for EarthSciML system
The Julia photochemical model is based on a Fortran photochemical mechanism from Dr. Michael Kleeman's graduate course ECI241 on air quality modeling at University of California, Davis.
Algorithms for the transport of mass and energy in the environment