130 citations · 222 across the 2 of their papers we have counts for
Showing cs.PLShow all
3 papers · 1 filter
cs.PL2019★ 130 cited
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…
cs.PL2018
Fashionable Modelling with Flux
Michael Innes, Elliot Saba, Keno Fischer +6
Machine learning as a discipline has seen an incredible surge of interest in recent years due in large part to a perfect storm of new theory, superior tooling, renewed interest in…
cs.PL2018
Don't Unroll Adjoint: Differentiating SSA-Form Programs
Michael Innes
This paper presents reverse-mode algorithmic differentiation (AD) based on source code transformation, in particular of the Static Single Assignment (SSA) form used by modern compi…