References and Resources

[alexpron]

Here are few references and resources that are relevant for Spangy code integration into slam:

References

• original spangy paper
• sensitivity study

  Software resources

• outils décomposition spectrale sur Reuter, 2009
• autre outils décomposition spectrale M. Reuter

[alexpron]

Optimizing code performance by relying on Intel MKL library

numpy and scipy installation compiled with Intel MKL instead of usual OpenBLAS library are a bit more robust and faster especially for huge matrix operations (https://www.intel.com/content/www/us/en/developer/articles/technical/numpyscipy-with-intel-mkl.html) It may help us reduce eigen values computation times