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Pre-built implicit layer architectures with O(1) backprop, GPUs, and stiff+non-stiff DE solvers, demonstrating scientific machine learning (SciML) and physics-informed machine learning methods
Surrogate modeling and optimization for scientific machine learning (SciML)
Linear operators for discretizations of differential equations and scientific machine learning (SciML)
Automatic detection of sparsity in pure Julia functions for sparsity-enabled scientific machine learning (SciML)