algebra, automatic differentiation (auto-differentiation, autodiff, or AD), also called algorithmic differentiation, computational differentiation, is a...
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Stan (software) (section Automatic differentiation)
automatic differentiation to calculate gradients of the model, which is required by HMC, NUTS, L-BFGS, BFGS, and variational inference. The automatic...
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Methods Numerical Differentiation from wolfram.com NAG Library numerical differentiation routines Boost. Math numerical differentiation, including finite...
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Moritz Diehl: "CasADi - A symbolic package for automatic differentiation and optimal control". Recent Advances in Algorithmic Differentiation. 2012....
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In applied mathematics, Hessian automatic differentiation are techniques based on automatic differentiation (AD) that calculate the second derivative...
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Differentiable programming is a programming paradigm in which a numeric computer program can be differentiated throughout via automatic differentiation...
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together a modified version of autograd (automatic obtaining of the gradient function through differentiation of a function) and TensorFlow's XLA (Accelerated...
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\to \mathbb {C} } , that is complex-differentiable at a point x = a {\textstyle x=a} is automatically differentiable at that point, when viewed as a function...
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exploiting automatic differentiation (AD) to compute the required derivatives in the partial differential equations, a new class of differentiation techniques...
30 KB (3,760 words) - 14:01, 19 July 2024
Andreyevich Radul; Jeffrey Mark Siskind (20 February 2015). "Automatic differentiation in machine learning: a survey". arXiv:1502.05767 [cs.LG]. "Microsoft/caffe"...
26 KB (882 words) - 23:10, 8 June 2024