Author:
Martino L.,Elvira V.,Luengo D.,Corander J.
Publisher
Springer Science and Business Media LLC
Subject
Computational Theory and Mathematics,Statistics, Probability and Uncertainty,Statistics and Probability,Theoretical Computer Science
Reference56 articles.
1. Ali, A.M., Yao, K., Collier, T.C., Taylor, E., Blumstein, D., Girod, L.: An empirical study of collaborative acoustic source localization. In: Proceedings of the Information Processing in Sensor Networks (IPSN07), Boston (2007)
2. Andrieu, C., de Freitas, N., Doucet, A., Jordan, M.: An introduction to MCMC for machine learning. Mach. Learn. 50, 5–43 (2003)
3. Andrieu, C., Doucet, A., Holenstein, R.: Particle Markov chain Monte Carlo methods. J. R. Stat. Soc. B 72(3), 269–342 (2010)
4. Andrieu, C., Thoms, J.: A tutorial on adaptive mcmc. Stat. Comput. 18, 343373 (2015)
5. Beaujean, F., Caldwell, A.: Initializing adaptive importance sampling with Markov chains. arXiv:1304.7808 (2013)
Cited by
61 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献