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AD-Rosetta-Stone reviews and mentions
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Understanding Automatic Differentiation in 30 lines of Python
[1] https://github.com/qobi/AD-Rosetta-Stone/
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Autodidax: Jax Core from Scratch (In Python)
I find the solutions from https://github.com/qobi/AD-Rosetta-Stone/ to be very helpful, particularly for representing forward and backward mode automatic differentiation using a functional approach.
I used this code as inspiration for a functional-only (without references/pointers) in Mercury: https://github.com/mclements/mercury-ad
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qobi/AD-Rosetta-Stone is an open source project licensed under GNU General Public License v3.0 only which is an OSI approved license.
The primary programming language of AD-Rosetta-Stone is Scala.
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