Workshop Program

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Monday Morning, February 12

Foundations

8:45 Invited Presentation 1

• Stephen L. Campbell: Automatic Differentiation and Implicit Differential Equations

9:30 Session 1

• Detlef Laugwitz: A Centennial: Calculus with Infinitesimals since Levi-Civita

10:00 Coffee

10:30-12:30 Session 2

• Martin Berz: Calculus and Numerics on Levi-Civita Fields
  
• Khodr Shamseddine and Martin Berz: Exception Handling in Derivative Computation with Nonarchimedean Calculus
  
• Gordon Pusch: Jet Space as the Geometric Arena of Automatic Differentiation
  
• Kyoko Fuchi and Martin Berz: Remainder Differential Algebras and their Applications
  
• Robert M. Williams: Automatic Differentiation Applied to Multivariate Invariant Polynomials

12:30 PM Lunch

Monday Afternoon, February 12

Hybrid Approaches to Automatic Differentiation

2:00 Invited Presentation 2

• Thomas F. Coleman: Structure and Efficient Jacobian Calculation

2:45 Session 3

• Christian H. Bischof and Mohammad R. Haghighat: A Hierarchical Approach to Automatic Differentiation

3:15 PM Coffee

3:40-5:10 Session 4

• Bijan Mohammadi, Jean-Michel Male, and Nicole Rostaing-Schmidt: Direct and Reverse Modes of Automatic Differentiation of Programs for Inverse Problems: Application to Optimum Shapes Design
  
• Jochen Benary: Parallelism in the Reverse Mode
  
• Dominique Villard, Bruno Arnaldi, and Laurent Cogne: Direct and Reverse Differentiation Applied to Multibody Dynamics
  
• Peter Eberhard: The Adjoint Variable Method for the Sensitivity Analysis of Multibody Systems Interpreted as Continuous, Hybrid Form of Automatic Differentiation

Monday Evening, February 12

5:15 PM-7:00 PM Poster Session/Reception

• Jason Abate, Chris Bischof and Alan Carle: A Comparison of Automatic Differentiation Techniques for Computing Hessians
• Alan Carle: ADIFOR 2.0
  
• Jacob Beutel and Daniel Mickish: Synthetic Calculus in X-Ray System Design
• Eric J. Braude: Nondestructive Computational Differentiation
• Alan Carle and Mike Fagan: AD is not always A
• K. R. Chen and J. M. Dawson: A Neo-Finite-Difference Method for Electromagnetic Simulations
• Bart Childs and Tim McGuire: Computational Differentiation in BVPs in Ordinary Differential Equations
• Laurent Cogne: Differentiation-Guided Parallel Code Generation for Simulation of Multibody Rigid Systems
• B. Christianson, A. Davies, Lawrence.C.W. Dixon, and R. Roy: Giving Reverse Differentiation a Helping Hand
• L. Hernandez Encinas, F. Montoya Vitini and J. Munoz Masque: A New Proof of Faa' de Bruno's Formula
• Ilan Finci, Ziv Yaniv, and Michel Bercovier: A Code Generator for Automatic Differentiation of Algorithms Written in C/C++
• Herbert Fischer: Complexity of the Derivative
• Harley Flanders: Power Series Solutions of ODEs
• Andrei M. Finkelstein and Misha Koshelev: Case Studies of Choosing a Numerical Differentiation Method Under Uncertainty: Computer-Aided Design and Radiotelescope Network Design
• Andreas Griewank and Petra Henneberger: Rational Predictors based on AD for ODE Solving
• Paul Hovland: Automatic Differentiation of Parallel Languages
• Christian Bischof, Timothy L. Knauff Jr. and Po-Ting Wu: Parallelizing Time in a Leapfrog Scheme
• Narendra N. Kota and Jasbir S. Arora: Computational Methods for Design Sensitivity Analysis of Optimal Control Problems
• Vladik Kreinovich, Vladimir Dmitriev and Nina Zheludeva: Combining Numerical Differentiation and Monte Carlo Results in Faster Error Estimation
• Barney Krinsky: Antenna Beam Shaping Optimization
• Salma Kuhlmann: Exponentiation in Power Series Fields
• James M. McDonough: Economic Planning via Optimal Control - Synthetic Calculus Applied to Resource Management
• Leo Michelotti: MXYZPTLK, Version 4.0. A C++ Implementation of Automated Differentiation and Differential Algebra
• Richard D. Neidinger: Mathematica Series as a Computational Differentiation Tool
• Ikuo Ozaki, Fumihiko Kimura and Martin Berz: Higher-Order Sensitivity Analysis of Mechanical Structure by Differential Algebraic Method
• Christian Bischof, Andrew Mauer and Lucas Roh: ADIC: A Robust Tool for Automatic Differentiation of C
• Stephen P. Smith: The Cholesky Decomposition and its Derivatives
• A. C. Taylor III, Lawrence L. Green, P.A. Newman: Automatic Differentiation of the CFL3D Flow Code in Incremental Iterative Form
• Alexander Tovbis: Numerical Integration of ODE's and Chaos-Integrability Transition
• Andreas Griewank and Jean Utke: Evaluating Higher Derivative Tensors through Univariate Taylor Polynomials
• Ronald Van Iwaarden: Faster Global Optimization through BackBoxing
• Dominique Villard: Dependency Graph, Reverse Differentiation and Functions: Problems and Tools
• Zhi Wang and Kelvin Droegemeier: Wind, Pressure and Thermodynamic Retrieval from Single-Dopplar Radar Data Using a 3-D Compressible Storm-Scale Model
• Zhi Wang, L. White, and K. Droegemeier: A Generalization of Le Dimet and Ngodock's Optimal Sensitivity Analysis of Physical Parameters in the Presence of Data
• Toshinobu Yoshida: A Node Elimination Rule for the Calculation of Jacobian Matrices
• Thomas F. Coleman and Arun Verma: The Efficient Compulation of Sparse Jacobians Using Automatic Differentiation

Tuesday Morning, February 13

Software for Computational Differentiation

8:45 Invited Presentation 3

• Michael Monagan: Automatic Differentiation in Computer Algebra Systems: An Implementation of the Forward and Reverse mode in Maple

9:30 Session 5

• Martin Berz, Kyoko Fuchi, Khodr Shamseddine, George H. Hoffstatter, and Weishi Wan: COSY INFINITY and its Applications to Nonlinear Dynamics

9:50 Coffee

10:20-12:00 Session 6

• Christian Bischof and Alan Carle: Experiences with ADIFOR 2.0
• Christian Bischof, Lucas Roh and Alan Carle: Building a Workbench for AD Tools and the Redesign of ADIC
• Koichi Kubota: Padre2 - Fortran Precompiler for Automatic Differentiation and Estimates of Rounding Errors
• Uwe Naumann and Wolfgang V. Walter: A Fortran 90 Automatic Differentiation Package for Verified Global Optimization
• Wolfram Klein: Comparisons of Different Automatic Differentiation Tools to Circuit Simulation

12:00 Lunch

Tuesday Afternoon, February 13

Weather Modeling

2:00 Invited Presentation

• Olivier Talagrand: Applications of Computational Differentiation in Numerical Modelling of the Atmospheric and Oceanic Circulation

2:45 Session 7

• Victor V. Goldman and Gerard Cats: Automatic Adjoint Modeling within a Program Generation Framework: A Case Study for a Weather Forecasting Grid Point Model

3:15 Coffee

3:40-5:10 Session 8

• Zhi Wang, Kelvin Droegemeier and L. White: The Adjoint Newton Algorithm for Large-Scale Unconstrained Optimization in Meteorology Applications
• Seon Ki Park, Kelvin K. Droegemeier and Christian Bischof: Automatic Differentiation as a Tool for Sensitivity Analysis of a Convective Storm in a 3-D Cloud Model
• Francois-Xavier Le Dimet and Michael Navon: Second Order Analysis in Variational Data Assimilation
• Anne K. Griffith and Nancy K. Nichols: Accounting for Model Error in Data Assimilation using Adjoint Models

Tuesday Evening, February 13

More Software for Computational Differentiation

7:30 Session 9

• Joseph Thames: The Meta-Calculus Vision
• Lawrence L. Green, P. A. Newman, and K. J. Haigler: Applications of Automatic Differentiation in Multidisciplinary Design Optimization
• William F. Feehery and Paul I. Barton: A Differentiation-Based Approach to Simulation and Dynamic Optimization with High-Index Differential-Algebraic Equations
• David M. Gay: More AD of Nonlinear AMPL Models: Computing Hessian Information and Exploiting Partial Seperability
• Dmitri Shiriaev: ADOL-F Automatic Differentiation of FORTRAN Codes
• George F. Corliss: ATOMFT: Automatic Differentiation for Solving Ordinary Differential Equations

Wednesday Morning, February 14

Differentiation of Nonsmooth Functions

8:45 Invited Presentation 5

• Ulrich Kulisch: Numerical Integration with Verification

9:30-10:20 Session 10

• Francis H. Clarke and Yuri S. Ledyaev: How to Use Derivatives to Estimate Extremal Values of the Function on Convex Sets
• Andreas Griewank and Manfred Fruth: One-sided Taylor-expansions and Generalized Gradients of Nonsmooth Functions by Automatic Differentiation

10:20 Coffee

10:50-12:30 Session 11

• Andre Galligo and Eric Hassold: Automatic Differentiation Applied to Nonsmooth Convex Optimization
• Frederic Eyssette and Vladimir Vyskocil: Round-off Error Analysis with Odyssee
• Baker Kearfott: Automatic Differentiation of Conditional Branches in an Operator Overloading Context
• Andrew Mauer, Christian Bischof and Alan Carle: The ADIntrinsics System for Handling Nonsmooth Intrinsics in the Automatic Differentiation of Fortran 77 Programs
• Alan Carle and Mike Fagan: Improving Derivative Performance for CFD Using Simplified Recurrences

12:30 Lunch

Wednesday Evening, February 14

Odyssee/Differential Equations

7:00 Session 12

• Jose Grimm, Loic Pottier and Nicole Rostaing-Schmidt: Optimal Time and Minimum Space Time Product for Reversing a Certain Class of Programs

7:30-8:50 Session 13

• Pierre Aubert and Eric Hassold: Computer Algebra System versus Automatic Differentiation for Shape Optimization of a Non-linear Arch
• Christel Faure: Splitting of Algebraic Expressions for Automatic Differentiation
• Alexander Shevchenko: Algebra of Differential Tuples for Computational Differentiation in Boundary Value Problems
• Philip H. Young and Charles A. Crummer: Oil Tanker Unloading: Optimization with Implicit Differential Equations

Thursday Morning, February 15

Sparse Jacobians and Hessians

8:45 Invited Presentation 6

• John Guckenheimer: Bifurcations, Automatic Differentiation and Computer Generated Proofs

9:30 Session 14

• Uwe Geitner, Andreas Griewank and Jean Utke: Sparse Jacobians by Newsam/Ramsdell

10:00 Coffee

10:30-12:00 Session 15

• Bruce Christianson: Sharing Storage Using Dirty Vectors
• Peyvand M. Khademi and Christian H. Bischof: Dynamically Exploiting Sparsity in Computing Jacobians - Implementation, Visualization and Examples
• A.K.M. Shabadat Hossain and Trond Steihaug: A Graph Coloring Approach to the Estimation of Sparse Jacobian Matrix and Row and Column Computation
• Guy Chavent, Jerome Jaffre, and Sophie Jegou and Jun Liu: A Symbolic Code Generator for Computing Gradients

12:00 Lunch

Thursday Afternoon, February 15

Applications

2:00 Invited Presentation 7

• William W. Symes: Adjoint Computations for Wave Propagation

2:45 Session 16

• David W. Juedes and Karthik Balakrishnan: Generalized Neural Networks, Computational Differentiation, and Evolution

3:15 Coffee

3:40-5:00 Session 17

• Jean Utke: Efficient Newton Steps without Jacobians
• Ulf W. Hutschenreiter: A New Method for Bevel Gear Tooth Flank Computation
• Max Jerrell: Automatic Differentiation and Interval Arithmetic for Estimation of Econometric Functions
• John Tolsma and Paul I. Barton: Systematic Approaches for Finding Multiple Local Optima in Nonconvex Nonlinear Programming Problems

5:00 Conference Adjourns