Computation Graphs for AAD and Machine Learning: Part II: Adjoint Differentiation and AAD
Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning
Second 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.
Originalsprog | Engelsk |
---|---|
Tidsskrift | Wilmott |
Udgave nummer | 105 |
Sider (fra-til) | 32–45 |
ISSN | 1540-6962 |
DOI | |
Status | Udgivet - 2020 |
ID: 250166510