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YouTubeChris Rackauckas
The Numerical Analysis of Differentiable Simulation: Automatic Differentiation Can Be Incorrect
Scientific machine learning (SciML) relies heavily on automatic differentiation (AD), the process of constructing gradients which include machine learning integrated into mechanistic models for the purpose of gradient-based optimization. While these differentiable programming approaches pitch an idea of "simply put the simulator into a loss ...
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