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GTApprox benchmark

These are scripts and data we used to compare GTApprox against several popular approximation libraries, as described in the paper GTApprox: surrogate modeling for industrial design (journal publication, arXiv preprint).

RRMS error profile Training time profile

Run runAllTests.py to save results for all individual tests. (Each test is run in a separate process by first restricting available virtual memory (with ulimit, Linux-only) and then calling the script runSingleTest.py.) After completion, run plotResults.py to collect results and plot performance profiles.

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Code and data for benchmark of GTApprox

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  • MATLAB 50.6%
  • Python 49.4%