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Found 3 papers, 3 papers with code
A Differentiable Programming System to Bridge Machine Learning and Scientific Computing
Scientific computing is increasingly incorporating the advancements in machine learning and the ability to work with large amounts of data.
DiffEqFlux.jl - A Julia Library for Neural Differential Equations
We show high-level functionality for defining neural ordinary differential equations (neural networks embedded into the differential equation) and describe the extra models in the Flux model zoo which includes neural stochastic differential equations.
A Comparison of Automatic Differentiation and Continuous Sensitivity Analysis for Derivatives of Differential Equation Solutions
In this manuscript we investigate the performance characteristics of Discrete Local Sensitivity Analysis implemented via Automatic Differentiation (DSAAD) against continuous adjoint sensitivity analysis.
Numerical Analysis
