3 papers
math.NA2025
Differentiable Programming for Differential Equations: A Review
Facundo Sapienza, Jordi Bolibar, Frank Schäfer +8
The differentiable programming paradigm is a cornerstone of modern scientific computing. It refers to numerical methods for computing the gradient of a numerical model's output. Ma…
cs.LG2025
Semi-Explicit Neural DAEs: Learning Long-Horizon Dynamical Systems with Algebraic Constraints
Avik Pal, Alan Edelman, Christopher Rackauckas
Despite the promise of scientific machine learning (SciML) in combining data-driven techniques with mechanistic modeling, existing approaches for incorporating hard constraints in…
math.NA2025
NonlinearSolve.jl: High-Performance and Robust Solvers for Systems of Nonlinear Equations in Julia
Avik Pal, Flemming Holtorf, Axel Larsson +6
Efficiently solving nonlinear equations underpins numerous scientific and engineering disciplines, yet scaling these solutions for challenging system models remains a challenge. Th…