Hennig, Philipp Max Planck Research Group Probabilistic Numerics, Max Planck Institute for Intelligent Systems, Max Planck Society; External Organizations;
https://proceedings.neurips.cc/paper_files/paper/2021/hash/9be40cee5b0eee1462c82c6964087ff9-Abstract.html (Publisher version)
https://doi.org/10.48550/arXiv.2010.02709 (Preprint)
https://openreview.net/forum?id=J-pFhOiGVn7 (Any fulltext)
Kristiadi, A., Hein, M., & Hennig, P. (2022). An Infinite-Feature Extension for Bayesian ReLU Nets That Fixes Their Asymptotic Overconfidence. In M. Ranzato, A. Beygelzimer, Y. Dauphin, P. Liang, & J. Wortman Vaughan (Eds.), Advances in Neural Information Processing Systems 34 (pp. 18789-18800). Red Hook, NY: Curran Associates, Inc. Retrieved from https://proceedings.neurips.cc/paper_files/paper/2021/hash/9be40cee5b0eee1462c82c6964087ff9-Abstract.html.
