IKPLS: Improved Kernel Partial Least Squares and Fast Cross-Validation Algorithms for Python with CPU and GPU Implementations Using NumPy and JAX

Python Submitted 25 January 2024 • Published 23 July 2024
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Authors

Ole-Christian Galbo Engstrøm (0000-0002-7906-4589), Erik Schou Dreier (0000-0001-9784-7504), Birthe Møller Jespersen (0000-0002-8695-1450), Kim Steenstrup Pedersen (0000-0003-3713-0960)

Citation

Engstrøm et al., (2024). IKPLS: Improved Kernel Partial Least Squares and Fast Cross-Validation Algorithms for Python with CPU and GPU Implementations Using NumPy and JAX. Journal of Open Source Software, 9(99), 6533, https://doi.org/10.21105/joss.06533

@article{Engstrøm2024, doi = {10.21105/joss.06533}, url = {https://doi.org/10.21105/joss.06533}, year = {2024}, publisher = {The Open Journal}, volume = {9}, number = {99}, pages = {6533}, author = {Ole-Christian Galbo Engstrøm and Erik Schou Dreier and Birthe Møller Jespersen and Kim Steenstrup Pedersen}, title = {IKPLS: Improved Kernel Partial Least Squares and Fast Cross-Validation Algorithms for Python with CPU and GPU Implementations Using NumPy and JAX}, journal = {Journal of Open Source Software} }
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PLS latent variables multivariate statistics cross-validation deep learning

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