Publication: Computational Differentiation: Techniques, Applications and Tools
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Computational Differentiation: Techniques, Applications and Tools

- Proceeding -


Martin Berz, Christian Bischof, George Corliss, Andreas Griewank



AD Theory and Techniques

Contained Articles
- A Differentiation-Based Approach to Dynamic Simulation and Optimization with High-Index Differential-Algebraic Equations
- A New Method for Bevel Gear Tooth Flank Computation
- A Symbolic Code Generator for Parameter Estimation
- Accounting for Model Error in Data Assimilation Using Adjoint Models
- Adjoint Variable Method for the Sensitivity Analysis of Multibody Systems Interpreted as Continuous, Hybrid Form of Automatic Differentiation
- ADOL--F Automatic Differentiation of Fortran Codes
- An Implementation of the Forward and Reverse mode in Maple
- An Introduction to Automatic Differentiation
- Automatic Adjoint Modeling within a Program Generation Framework: A Case Study for a Weather Forecasting Grid-Point Model
- Automatic Computation of Sparse Jacobians by Applying the Method of Newsam and Ramsdell
- Automatic Differentiation and Implicit Differential Equations
- Automatic Differentiation and Interval Arithmetic for Estimation of Econometric Functions
- Automatic Differentiation Applied to Convex Optimization
- Automatic Differentiation as a Tool for Sensitivity Analysis of a Convective Storm in a 3-D Cloud Model
- Automatic Differentiation in Direct and Reverse Modes: Application to Optimum Shapes Design in Fluid Mechanics
- Automatic Differentiation of Conditional Branches in an Operator Overloading Context
- Automatic Differentiation: An Implementation of the Forward and Reverse mode in Maple
- Bibliography of Computational Differentiation
- Bifurcations, Automatic Differentiation and Computer Generated Proofs
- Calculus and Numerics on Levi-Civita Fields
- Comparisons of Automatic Differentiation Tools in Circuit Simulation
- Computer Proofs for Bifurcations of Planar Dynamical Systems
- COSY INFINITY and Its Applications in Nonlinear Dynamics
- Efficient Newton Steps without Jacobians
- Exception Handling in Derivative Computation with Nonarchimedean Calculus
- Generalized Neural Networks, Computational Differentiation, and Evolution
- Hierarchical Approaches to Automatic Differentiation
- Improving Derivative Performance for CFD by Using Simplified Recurrences
- Jet Space as the Geometric Arena of Automatic Differentiation
- More AD of Nonlinear AMPL Models: Computing Hessian Information and Exploiting Partial Separability
- Optimal Time and Minimum Space-Time Product for Reversing a Certain Class of Programs
- PADRE2 -- Fortran Precompiler for Automatic Differentiation and Estimates of Rounding Errors
- Parallelism in the Reverse Mode
- Remainder Differential Algebras and their Applications
- Sharing Storage Using Dirty Vectors
- Splitting of Algebraic Expressions for Automatic Differentiation
- Structure and Efficient Jacobian Calculation
- Users' Experience with ADIFOR 2.0

       editor = "Martin Berz and Christian Bischof and George Corliss and Andreas Griewank",
       title = "Computational Differentiation: Techniques, Applications and Tools",
       publisher = "SIAM",
       address = "Philadelphia, PA",
       comment = "Proceedings of the SIAM Workshop on the Automatic Differentiation of Algorithms in
         Santa Fe, New Mexico, February 12 -- 14, 1996.",
       isbn = "0--89871--385--4",
       year = "1996",
       ad_theotech = "General"


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