495 citations · 1.5k across the 56 of their papers we have counts for
4 papers · 1 filter
A Differentiable Programming System to Bridge Machine Learning and Scientific Computing
Mike Innes, Alan Edelman, Keno Fischer +4
Scientific computing is increasingly incorporating the advancements in machine learning and the ability to work with large amounts of data. At the same time, machine learning model…
Parallel Prefix Polymorphism Permits Parallelization, Presentation & Proof
Jiahao Chen, Alan Edelman
Polymorphism in programming languages enables code reuse. Here, we show that polymorphism has broad applicability far beyond computations for technical computing: parallelism in di…
Array operators using multiple dispatch: a design methodology for array implementations in dynamic languages
Jeff Bezanson, Jiahao Chen, Stefan Karpinski +2
Arrays are such a rich and fundamental data type that they tend to be built into a language, either in the compiler or in a large low-level library. Defining this functionality at…
Julia: A Fast Dynamic Language for Technical Computing
Jeff Bezanson, Stefan Karpinski, Viral B. Shah +1
Dynamic languages have become popular for scientific computing. They are generally considered highly productive, but lacking in performance. This paper presents Julia, a new dynami…