Read more at: Reflections on the 27th EuroAD workshop
Reflections on the 27th EuroAD workshop
14 May 2025
Derivatives are at the core of scientific computing: from the Jacobian matrices used in nonlinear solvers to the gradient vectors used in optimisation methods; from the back-propagation operator in machine learning (ML) to the Hessian matrices used in uncertainty quantification methods. Automatic differentiation (AD) -...