Javier Antorán, David Janz, James Urquhart Allingham, Erik A. Daxberger, Riccardo Barbano, Eric T. Nalisnick, José Miguel Hernández-Lobato. Adapting the Linearised Laplace Model Evidence for Modern Deep Learning. In Kamalika Chaudhuri, Stefanie Jegelka, Le Song, Csaba Szepesvári, Gang Niu 0001, Sivan Sabato, editors, International Conference on Machine Learning, ICML 2022, 17-23 July 2022, Baltimore, Maryland, USA. Volume 162 of Proceedings of Machine Learning Research, pages 796-821, PMLR, 2022. [doi]
@inproceedings{AntoranJADBNH22,
title = {Adapting the Linearised Laplace Model Evidence for Modern Deep Learning},
author = {Javier Antorán and David Janz and James Urquhart Allingham and Erik A. Daxberger and Riccardo Barbano and Eric T. Nalisnick and José Miguel Hernández-Lobato},
year = {2022},
url = {https://proceedings.mlr.press/v162/antoran22a.html},
researchr = {https://researchr.org/publication/AntoranJADBNH22},
cites = {0},
citedby = {0},
pages = {796-821},
booktitle = {International Conference on Machine Learning, ICML 2022, 17-23 July 2022, Baltimore, Maryland, USA},
editor = {Kamalika Chaudhuri and Stefanie Jegelka and Le Song and Csaba Szepesvári and Gang Niu 0001 and Sivan Sabato},
volume = {162},
series = {Proceedings of Machine Learning Research},
publisher = {PMLR},
}