Provenance Tracking for End-to-End Machine Learning Pipelines.

@inproceedings{grafberger-2023-provenance, author = {Stefan Grafberger and Paul Groth and Sebastian Schelter}, editor = {Ying Ding and Jie Tang and Juan F. Sequeda and Lora Aroyo and Carlos Castillo and Geert-Jan Houben}, title = {{Provenance Tracking for End-to-End Machine Learning Pipelines}}, booktitle = {{Companion Proceedings of the ACM Web Conference 2023, WWW 2023, Austin, TX, USA, 30 April 2023 - 4 May 2023}}, pages = {1512}, publisher = {ACM}, year = {2023}, url = {https://doi.org/10.1145/3543873.3587557}, doi = {https://doi.org/10.1145/3543873.3587557} }