2 papers
cs.MS2025
A Common Interface for Automatic Differentiation
Guillaume Dalle, Adrian Hill
For scientific machine learning tasks with a lot of custom code, picking the right Automatic Differentiation (AD) system matters. Our Julia package DifferentiationInterfacejl pr…
cs.LG2025
Sparser, Better, Faster, Stronger: Sparsity Detection for Efficient Automatic Differentiation
Adrian Hill, Guillaume Dalle
From implicit differentiation to probabilistic modeling, Jacobian and Hessian matrices have many potential use cases in Machine Learning (ML), but they are viewed as computationall…