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A general-purpose probabilistic programming system with programmable inference
Curated decibans of scientific programming resources in Python.
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
Submit and execute distributed computations. A dask.distributed scheduler and Dispatcher.jl integration.