Automatic differentiation : applications, theory, and implementations
The Fourth International Conference on Automatic Differentiation was held July 20-23 in Chicago, Illinois.The conference included a one da short course, 42 presentations, and a workshop for tool developers. This gathering of automatic differentiation researchers extended a sequence that began in Bre...
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| Collectivité auteur: | |
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| Autres auteurs: | , , , , |
| Format: | Livre numérique |
| Langue: | Anglais |
| Publié: |
Berlin, Heidelberg :
Springer Berlin Heidelberg
[20..].
Cham : Springer Nature |
| Édition: | 1st ed. 2006. |
| Collection: | Lecture Notes in Computational Science and Engineering
50 |
| Sujets: | |
| Accès en ligne: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Note: |
Description d'après consultation du 10 mars 2011 Autres contributions : Uwe Naumann, Boyana Norris (editors) Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Automatic Differentiation: Applications, Theory, and Implementations, Texte imprimé, 9783540814580 • Automatic differentiation, applications, theory and implementations, Martin Bücker, George Corliss, Paul Hovland... [et al.], eds, 2006, Berlin, Springer, 1 vol. (XVII-361 p.), Lecture notes in computational science and engineering, 978-3-540-28403-1 |
Table des matières:
- 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