dual
Automatic Differentiation with Dual Numbers
Automatic differentiation is achieved by using dual numbers without providing hand-coded gradient functions. The output value of a mathematical function is returned with the values of its exact first derivative (or gradient). For more details see Baydin, Pearlmutter, Radul, and Siskind (2018) <https://jmlr.org/papers/volume18/17-468/17-468.pdf>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.0.6 |
rolling source/ R- | dual_0.0.6.tar.gz |
31.7 KiB |
0.0.6 |
latest source/ R- | dual_0.0.6.tar.gz |
31.7 KiB |
0.0.6 |
2026-04-09 windows/windows R-4.5 | dual_0.0.6.zip |
241.7 KiB |