Sara Wade - Leveraging variational autoencoders for multiple data

Conference paper

Breeshey Roskams-Hieter, Jude Wells, Sara Wade
Proceedings of the European Conference on Machine Learning (ECML-PKDD) 2023, Springer Lecture Notes in Computer Science

DOI: 10.1007/978-3-031-43412-9_29

Github Paper

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APA Click to copy
Roskams-Hieter, B., Wells, J., & Wade, S. Leveraging variational autoencoders for multiple data imputation. In Proceedings of the European Conference on Machine Learning (ECML-PKDD) 2023. Springer Lecture Notes in Computer Science. https://doi.org/10.1007/978-3-031-43412-9_29

Chicago/Turabian Click to copy
Roskams-Hieter, Breeshey, Jude Wells, and Sara Wade. “Leveraging Variational Autoencoders for Multiple Data Imputation.” In Proceedings of the European Conference on Machine Learning (ECML-PKDD) 2023. Springer Lecture Notes in Computer Science, n.d.

MLA Click to copy
Roskams-Hieter, Breeshey, et al. “Leveraging Variational Autoencoders for Multiple Data Imputation.” Proceedings of the European Conference on Machine Learning (ECML-PKDD) 2023, Springer Lecture Notes in Computer Science, doi:10.1007/978-3-031-43412-9_29.

BibTeX Click to copy

@inproceedings{breeshey-a,
  title = {Leveraging variational autoencoders for multiple data imputation},
  journal = {Proceedings of the European Conference on Machine Learning (ECML-PKDD) 2023},
  publisher = {Springer  Lecture Notes in Computer Science},
  doi = {10.1007/978-3-031-43412-9_29},
  author = {Roskams-Hieter, Breeshey and Wells, Jude and Wade, Sara}
}