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.