Computation Graphs for AAD and Machine Learning: Part I: Introduction to Computation Graphs and Automatic Differentiation
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Computation Graphs for AAD and Machine Learning : Part I: Introduction to Computation Graphs and Automatic Differentiation. / Savine, Antoine.
I: Wilmott, Nr. 104, 2019, s. 36-61.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
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RIS
TY - JOUR
T1 - Computation Graphs for AAD and Machine Learning
T2 - Part I: Introduction to Computation Graphs and Automatic Differentiation
AU - Savine, Antoine
PY - 2019
Y1 - 2019
N2 - First in a series of three articles with code, exploring the notion of computation graph, with words mathematics and code, and application in Machine Learning and finance to compute a vast number of derivative sensitivities with spectacular speed and accuracy.
AB - First in a series of three articles with code, exploring the notion of computation graph, with words mathematics and code, and application in Machine Learning and finance to compute a vast number of derivative sensitivities with spectacular speed and accuracy.
U2 - 10.1002/wilm.10804
DO - 10.1002/wilm.10804
M3 - Journal article
SP - 36
EP - 61
JO - Wilmott
JF - Wilmott
SN - 1540-6962
IS - 104
ER -
ID: 250165759