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[1-5]
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[Title],
[Author],
[Editor],
[Year] |
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Benjamin Letschert, Kshitij Kulshreshtha, Andrea Walther, Duc Nguyen, Assefaw Gebremedhin, Alex Pothen
Exploiting Sparsity in Automatic Differentiation on Multicore Architectures
Recent Advances in Algorithmic Differentiation, Springer,
2012 |
Theory & Techniques:
Parallelism, Sparsity
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Kshitij Kulshreshtha, Jan Marburger
Computing Derivatives in a Meshless Simulation Using Permutations in ADOL-C
Recent Advances in Algorithmic Differentiation, Springer,
2012 |
Tools:
ADOL-C
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Andreas Griewank, Kshitij Kulshreshtha, Andrea Walther
On the numerical stability of algorithmic differentiation
Article in
Computing, Springer Vienna,
2012 |
Theory & Techniques:
Stability
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Sabrina Fiege, Andrea Walther, Kshitij Kulshreshtha, Andreas Griewank
Algorithmic differentiation for piecewise smooth functions: a case study for robust optimization
Article in
Special issue of Optimization Methods & Software: Advances in Algorithmic Differentiation, Taylor & Francis,
2018 |
not yet classified
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Kshitij Kulshreshtha, Sri Hari Krishna Narayanan, Julie Bessac, Kaitlyn MacIntyre
Efficient computation of derivatives for solving optimization problems in R and Python using SWIG-generated interfaces to ADOL-C
Article in
Special issue of Optimization Methods & Software: Advances in Algorithmic Differentiation, Taylor & Francis,
2018 |
not yet classified
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