algebra, automatic differentiation (auto-differentiation, autodiff, or AD), also called algorithmic differentiation, computational differentiation, is a...

In applied mathematics, Hessian automatic differentiation are techniques based on automatic differentiation (AD) that calculate the second derivative...

Methods Numerical Differentiation from wolfram.com NAG Library numerical differentiation routines Boost. Math numerical differentiation, including finite...

Moritz Diehl: "CasADi - A symbolic package for automatic differentiation and optimal control". Recent Advances in Algorithmic Differentiation. 2012....

}}\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...

Differentiable programming is a programming paradigm in which a numeric computer program can be differentiated throughout via automatic differentiation...

automatic differentiation to calculate gradients of the model, which is required by HMC, NUTS, L-BFGS, BFGS, and variational inference. The automatic...

together a modified version of autograd (automatic obtaining of the gradient function through differentiation of a function) and TensorFlow's XLA (Accelerated...

exploiting automatic differentiation (AD) to compute the required derivatives in the partial differential equations, a new class of differentiation techniques...

Andreyevich Radul; Jeffrey Mark Siskind (20 February 2015). "Automatic differentiation in machine learning: a survey". arXiv:1502.05767 [cs.LG]. "Microsoft/caffe"...