checkpointed-steps

Introduction

This package defines a large amount of ready to use components for the checkpointed library.

References

This section provides a list of papers which were used for the development of checkpointed-steps, or describe one of the underlying dependencies used.

[1] Pedregosa et al., Scikit-learn: Machine Learning in Python, JMLR 12, pp. 2825-2830, 2011.

[2] McInnes et al., UMAP: Uniform Manifold Approximation and Projection. Journal of Open Source Software, 3(29), 861, 2018.

[3] Nils Reimers and Iryna Gurevych, Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks, 2019

References in Bib format

@article{scikit-learn,
    title={Scikit-learn: Machine Learning in {P}ython},
    author={Pedregosa, F. and Varoquaux, G. and Gramfort, A. and Michel, V.
         and Thirion, B. and Grisel, O. and Blondel, M. and Prettenhofer, P.
         and Weiss, R. and Dubourg, V. and Vanderplas, J. and Passos, A. and
         Cournapeau, D. and Brucher, M. and Perrot, M. and Duchesnay, E.},
    journal={Journal of Machine Learning Research},
    volume={12},
    pages={2825--2830},
    year={2011}
}

@article{McInnes2018, 
    doi = {10.21105/joss.00861}, 
    url = {https://doi.org/10.21105/joss.00861}, 
    year = {2018}, 
    publisher = {The Open Journal}, 
    volume = {3}, 
    number = {29}, 
    pages = {861}, 
    author = {Leland McInnes and John Healy and Nathaniel Saul and Lukas Großberger}, 
    title = {UMAP: Uniform Manifold Approximation and Projection}, 
    journal = {Journal of Open Source Software}
} 

@misc{reimers2019sentencebert,
      title={Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks}, 
      author={Nils Reimers and Iryna Gurevych},
      year={2019},
      eprint={1908.10084},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}