Computation Graphs for AAD and Machine Learning: Part II: Adjoint Differentiation and AAD
Research output: Contribution to journal › Journal article
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.
Original language | English |
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Journal | Wilmott |
Issue number | 105 |
Pages (from-to) | 32–45 |
ISSN | 1540-6962 |
DOIs | |
Publication status | Published - 2020 |
ID: 250166510