CORDIS Project
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This project develops a framework for automatic differentiation in programming languages that support complex features like higher-order functions. It aims to provide formal correctness proofs for these techniques using advanced mathematical concepts, ensuring reliable implementations for computational tasks.
Many recent advances in machine learning and computational statistics rely on algorithms that calculate derivatives.
This use of derivatives has motivated the creation of domain specific modelling languages in which each program can be differentiated automatically, by the compiler.
This technique is known as automatic differentiation (AD). AD is typically implemented through source-code-transformations, either directly or indirectly via operator overloading.
These transformations become intricat…
UNIVERSITEIT UTRECHT
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