algebra, automatic differentiation (auto-differentiation, autodiff, or AD), also called algorithmic differentiation, computational differentiation, is a...
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Methods Numerical Differentiation from wolfram.com NAG Library numerical differentiation routines Boost. Math numerical differentiation, including finite...
17 KB (2,280 words) - 17:55, 26 June 2024
Differentiable programming is a programming paradigm in which a numeric computer program can be differentiated throughout via automatic differentiation...
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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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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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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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Moritz Diehl: "CasADi - A symbolic package for automatic differentiation and optimal control". Recent Advances in Algorithmic Differentiation. 2012....
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}}\right)=0} exists. However, for x ≠ 0 , {\displaystyle x\neq 0,} differentiation rules imply f ′ ( x ) = 2 x sin ( 1 / x ) − cos ( 1 / x ) , {\displaystyle...
12 KB (1,675 words) - 18:25, 20 August 2024
Andreyevich Radul; Jeffrey Mark Siskind (20 February 2015). "Automatic differentiation in machine learning: a survey". arXiv:1502.05767 [cs.LG]. "Microsoft/caffe"...
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exploiting automatic differentiation (AD) to compute the required derivatives in the partial differential equations, a new class of differentiation techniques...
31 KB (3,875 words) - 23:29, 21 August 2024