ML Anthology

A Practical Monte Carlo Implementation of Bayesian Learning

Carl Edward Rasmussen
NeurIPS 1995 pp. 598-604
/neurips/1995/rasmussen1995neurips-practical/

Abstract

A practical method for Bayesian training of feed-forward neural networks using sophisticated Monte Carlo methods is presented and evaluated. In reasonably small amounts of computer time this approach outperforms other state-of-the-art methods on 5 data(cid:173) limited tasks from real world domains.

PDF NeurIPS Semantic Scholar

Cite

Text

Rasmussen. "A Practical Monte Carlo Implementation of Bayesian Learning." Neural Information Processing Systems, 1995.

Markdown

[Rasmussen. "A Practical Monte Carlo Implementation of Bayesian Learning." Neural Information Processing Systems, 1995.](https://mlanthology.org/neurips/1995/rasmussen1995neurips-practical/)

BibTeX

@inproceedings{rasmussen1995neurips-practical,
  title     = {{A Practical Monte Carlo Implementation of Bayesian Learning}},
  author    = {Rasmussen, Carl Edward},
  booktitle = {Neural Information Processing Systems},
  year      = {1995},
  pages     = {598-604},
  url       = {https://mlanthology.org/neurips/1995/rasmussen1995neurips-practical/}
}