Differenziazione automatica (Italian Wikipedia)

Analysis of information sources in references of the Wikipedia article "Differenziazione automatica" in Italian language version.

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1tensorflow.org

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1deeplearning.net

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archive.org

Žiga Sajovic e Martin Vuk, Operational calculus on programming spaces, 24 ottobre 2016.

davidson.edu

academics.davidson.edu

Richard D. Neidinger, Introduction to Automatic Differentiation and MATLAB Object-Oriented Programming (PDF), in SIAM Review, vol. 52, n. 3, 2010, pp. 545–563, DOI:10.1137/080743627.

deeplearning.net

Derivatives in Theano — Theano 1.0.0 documentation, su deeplearning.net.

doi.org

dx.doi.org

Richard D. Neidinger, Introduction to Automatic Differentiation and MATLAB Object-Oriented Programming (PDF), in SIAM Review, vol. 52, n. 3, 2010, pp. 545–563, DOI:10.1137/080743627.
R.E. Wengert, A simple automatic derivative evaluation program, in Comm. ACM, vol. 7, 1964, pp. 463–464, DOI:10.1145/355586.364791.
Michael Bartholomew-Biggs, Steven Brown, Bruce Christianson e Laurence Dixon, Automatic differentiation of algorithms ^{[collegamento interrotto]}, in Journal of Computational and Applied Mathematics, vol. 124, n. 1-2, 2000, pp. 171–190, DOI:10.1016/S0377-0427(00)00422-2.
Uwe Naumann, Optimal Jacobian accumulation is NP-complete, in Mathematical Programming, vol. 112, n. 2, aprile 2008, pp. 427–441, DOI:10.1007/s10107-006-0042-z.

els-cdn.com

ac.els-cdn.com

Michael Bartholomew-Biggs, Steven Brown, Bruce Christianson e Laurence Dixon, Automatic differentiation of algorithms ^{[collegamento interrotto]}, in Journal of Computational and Applied Mathematics, vol. 124, n. 1-2, 2000, pp. 171–190, DOI:10.1016/S0377-0427(00)00422-2.

oadoi.org

R.E. Wengert, A simple automatic derivative evaluation program, in Comm. ACM, vol. 7, 1964, pp. 463–464, DOI:10.1145/355586.364791.
Uwe Naumann, Optimal Jacobian accumulation is NP-complete, in Mathematical Programming, vol. 112, n. 2, aprile 2008, pp. 427–441, DOI:10.1007/s10107-006-0042-z.

pytorch.org

Automatic differentiation package - torch.autograd, su pytorch.org.

tensorflow.org

Eager Execution, su tensorflow.org.