Automatic Differentiation: Applications, Theory, and Implementations

- Perspectives on Automatic Differentiation: Past, Present, and Future?

- Backwards Differentiation in AD and Neural Nets: Past Links and New Opportunities

- Solutions of ODEs with Removable Singularities

- Automatic Propagation of Uncertainties

- High-Order Representation of Poincarée Maps

- Computation of Matrix Permanent with Automatic Differentiation

- Computing Sparse Jacobian Matrices Optimally

- Application of AD-based Quasi-Newton Methods to Stiff ODEs

- Reduction of Storage Requirement by Checkpointing for Time-Dependent Optimal Control Problems in ODEs

- Improving the Performance of the Vertex Elimination Algorithm for Derivative Calculation

- Flattening Basic Blocks

- The Adjoint Data-Flow Analyses: Formalization, Properties, and Applications

- Semiautomatic Differentiation for Efficient Gradient Computations

- Computing Adjoints with the NAGWare Fortran 95 Compiler

- Transforming Equation-Based Models in Process Engineering

- Extension of TAPENADE toward Fortran 95

- A Macro Language for Derivative Definition in ADiMat

- Simulation and Optimization of the Tevatron Accelerator

- Periodic Orbits of Hybrid Systems and Parameter Estimation via AD

- Implementation of Automatic Differentiation Tools for Multicriteria IMRT Optimization

- Application of Targeted Automatic Differentiation to Large-Scale Dynamic Optimization

- Automatic Differentiation: A Tool for Variational Data Assimilation and Adjoint Sensitivity Analysis for Flood Modeling

- Development of an Adjoint for a Complex Atmospheric Model, the ARPS, using TAF

- Tangent Linear and Adjoint Versions of NASA/GMAO's Fortran 90 Global Weather Forecast Model

- Efficient Sensitivities for the Spin-Up Phase

- Streamlined Circuit Device Model Development with fREEDAR® ãnd ADOL-C

- Adjoint Differentiation of a Structural Dynamics Solver

- A Bibliography of Automatic Differentiation