Distilling BlackBox to Interpretable Models for Efficient Transfer Learning

Shantanu Ghosh, Ke Yu, Kayhan Batmanghelich. Distilling BlackBox to Interpretable Models for Efficient Transfer Learning. In Hayit Greenspan, Anant Madabhushi, Parvin Mousavi, Septimiu Salcudean, James Duncan 0001, Tanveer F. Syeda-Mahmood, Russell H. Taylor, editors, Medical Image Computing and Computer Assisted Intervention - MICCAI 2023 - 26th International Conference, Vancouver, BC, Canada, October 8-12, 2023, Proceedings, Part II. Volume 14221 of Lecture Notes in Computer Science, pages 628-638, Springer, 2023. [doi]

@inproceedings{GhoshYB23,
  title = {Distilling BlackBox to Interpretable Models for Efficient Transfer Learning},
  author = {Shantanu Ghosh and Ke Yu and Kayhan Batmanghelich},
  year = {2023},
  doi = {10.1007/978-3-031-43895-0_59},
  url = {https://doi.org/10.1007/978-3-031-43895-0_59},
  researchr = {https://researchr.org/publication/GhoshYB23},
  cites = {0},
  citedby = {0},
  pages = {628-638},
  booktitle = {Medical Image Computing and Computer Assisted Intervention - MICCAI 2023 - 26th International Conference, Vancouver, BC, Canada, October 8-12, 2023, Proceedings, Part II},
  editor = {Hayit Greenspan and Anant Madabhushi and Parvin Mousavi and Septimiu Salcudean and James Duncan 0001 and Tanveer F. Syeda-Mahmood and Russell H. Taylor},
  volume = {14221},
  series = {Lecture Notes in Computer Science},
  publisher = {Springer},
  isbn = {978-3-031-43895-0},
}