Abstract
Backwards calculation of derivatives – sometimes called the reverse mode, the full adjoint method, or backpropagation – has been developed and applied in many fields. This paper reviews several strands of history, advanced capabilities and types of application – particularly those which are crucial to the development of brain-like capabilities in intelligent control and artificial intelligence.
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© 2006 Springer
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Werbos, P.J. (2006). Backwards Differentiation in AD and Neural Nets: Past Links and New Opportunities. In: Bücker, M., Corliss, G., Naumann, U., Hovland, P., Norris, B. (eds) Automatic Differentiation: Applications, Theory, and Implementations. Lecture Notes in Computational Science and Engineering, vol 50. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-28438-9_2
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DOI: https://doi.org/10.1007/3-540-28438-9_2
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Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28403-1
Online ISBN: 978-3-540-28438-3
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