39 citations · 89 across the 16 of their papers we have counts for
3 papers · 1 filter
Confusion of Tagged Perturbations in Forward Automatic Differentiation of Higher-Order Functions
Oleksandr Manzyuk, Barak A. Pearlmutter, Alexey Andreyevich Radul +2
Forward Automatic Differentiation (AD) is a technique for augmenting programs to compute derivatives. The essence of Forward AD is to attach perturbations to each number, and propa…
AD in Fortran, Part 2: Implementation via Prepreprocessor
Alexey Radul, Barak A. Pearlmutter, Jeffrey Mark Siskind
We describe an implementation of the Farfel Fortran AD extensions. These extensions integrate forward and reverse AD directly into the programming model, with attendant benefits to…
AD in Fortran, Part 1: Design
Alexey Radul, Barak A. Pearlmutter, Jeffrey Mark Siskind
We propose extensions to Fortran which integrate forward and reverse Automatic Differentiation (AD) directly into the programming model. Irrespective of implementation technology,…