FSP-Laplace: Function-Space Priors for the Laplace Approximation in Bayesian Deep Learning

Tristan Cinquin, Marvin Pförtner, Vincent Fortuin, Philipp Hennig, Robert Bamler. FSP-Laplace: Function-Space Priors for the Laplace Approximation in Bayesian Deep Learning. In Amir Globersons, Lester Mackey, Danielle Belgrave, Angela Fan, Ulrich Paquet, Jakub M. Tomczak, Cheng Zhang 0005, editors, Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, NeurIPS 2024, Vancouver, BC, Canada, December 10 - 15, 2024. 2024. [doi]

@inproceedings{CinquinPFHB24,
  title = {FSP-Laplace: Function-Space Priors for the Laplace Approximation in Bayesian Deep Learning},
  author = {Tristan Cinquin and Marvin Pförtner and Vincent Fortuin and Philipp Hennig and Robert Bamler},
  year = {2024},
  url = {http://papers.nips.cc/paper_files/paper/2024/hash/19774ce2d4b0d17a3a8aea26ad99fe8a-Abstract-Conference.html},
  researchr = {https://researchr.org/publication/CinquinPFHB24},
  cites = {0},
  citedby = {0},
  booktitle = {Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, NeurIPS 2024, Vancouver, BC, Canada, December 10 - 15, 2024},
  editor = {Amir Globersons and Lester Mackey and Danielle Belgrave and Angela Fan and Ulrich Paquet and Jakub M. Tomczak and Cheng Zhang 0005},
}