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Arnaud Doucet: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Jaco Vermaak, Arnaud Doucet, Patrick Pérez
    Maintaining Multi-Modality through Mixture Tracking. [Citation Graph (0, 0)][DBLP]
    ICCV, 2003, pp:1110-1116 [Conf]
  2. Simon I. Hill, Arnaud Doucet
    Adapting two-class support vector classification methods to many class problems. [Citation Graph (0, 0)][DBLP]
    ICML, 2005, pp:313-320 [Conf]
  3. Mike Klaas, Mark Briers, Nando de Freitas, Arnaud Doucet, Simon Maskell, Dustin Lang
    Fast particle smoothing: if I had a million particles. [Citation Graph (0, 0)][DBLP]
    ICML, 2006, pp:481-488 [Conf]
  4. Shien-Shin Tham, Arnaud Doucet, Kotagiri Ramamohanarao
    Sparse Bayesian Learning for Regression and Classification using Markov Chain Monte Carlo. [Citation Graph (0, 0)][DBLP]
    ICML, 2002, pp:634-641 [Conf]
  5. Christophe Andrieu, Nando de Freitas, Arnaud Doucet
    Rao-Blackwellised Particle Filtering via Data Augmentation. [Citation Graph (0, 0)][DBLP]
    NIPS, 2001, pp:561-567 [Conf]
  6. Christophe Andrieu, João F. G. de Freitas, Arnaud Doucet
    Robust Full Bayesian Methods for Neural Networks. [Citation Graph (0, 0)][DBLP]
    NIPS, 1999, pp:379-385 [Conf]
  7. João F. G. de Freitas, Mahesan Niranjan, Arnaud Doucet, Andrew H. Gee
    Global Optimisation of Neural Network Models via Sequential Sampling. [Citation Graph (0, 0)][DBLP]
    NIPS, 1998, pp:410-416 [Conf]
  8. Rudolph van der Merwe, Arnaud Doucet, Nando de Freitas, Eric A. Wan
    The Unscented Particle Filter. [Citation Graph (0, 0)][DBLP]
    NIPS, 2000, pp:584-590 [Conf]
  9. Jaco Vermaak, Simon J. Godsill, Arnaud Doucet
    Sequential Bayesian Kernel Regression. [Citation Graph (0, 0)][DBLP]
    NIPS, 2003, pp:- [Conf]
  10. Christophe Andrieu, Nando de Freitas, Arnaud Doucet
    Reversible Jump MCMC Simulated Annealing for Neural Networks. [Citation Graph (0, 0)][DBLP]
    UAI, 2000, pp:11-18 [Conf]
  11. Arnaud Doucet, Nando de Freitas, Kevin P. Murphy, Stuart J. Russell
    Rao-Blackwellised Particle Filtering for Dynamic Bayesian Networks. [Citation Graph (0, 0)][DBLP]
    UAI, 2000, pp:176-183 [Conf]
  12. Christophe Andrieu, Nando de Freitas, Arnaud Doucet, Michael I. Jordan
    An Introduction to MCMC for Machine Learning. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 2003, v:50, n:1-2, pp:5-43 [Journal]
  13. Christophe Andrieu, Nando de Freitas, Arnaud Doucet
    Robust Full Bayesian Learning for Radial Basis Networks. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 2001, v:13, n:10, pp:2359-2407 [Journal]
  14. João F. G. de Freitas, Mahesan Niranjan, Andrew H. Gee, Arnaud Doucet
    Sequential Monte Carlo Methods to Train Neural Network Models. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 2000, v:12, n:4, pp:955-993 [Journal]
  15. Christophe Andrieu, Arnaud Doucet
    Simulated annealing for maximum a Posteriori parameter estimation of hidden Markov models. [Citation Graph (0, 0)][DBLP]
    IEEE Transactions on Information Theory, 2000, v:46, n:3, pp:994-1004 [Journal]
  16. Sumeetpal S. Singh, Vladislav B. Tadic, Arnaud Doucet
    A policy gradient method for semi-Markov decision processes with application to call admission control. [Citation Graph (0, 0)][DBLP]
    European Journal of Operational Research, 2007, v:178, n:3, pp:808-818 [Journal]
  17. Mike Klaas, Nando de Freitas, Arnaud Doucet
    Toward Practical N2 Monte Carlo: the Marginal Particle Filter. [Citation Graph (0, 0)][DBLP]
    UAI, 2005, pp:308-315 [Conf]

  18. Inference and Learning for Active Sensing, Experimental Design and Control. [Citation Graph (, )][DBLP]


  19. Sparse Bayesian nonparametric regression. [Citation Graph (, )][DBLP]


  20. Bayesian Policy Learning with Trans-Dimensional MCMC. [Citation Graph (, )][DBLP]


  21. Active Policy Learning for Robot Planning and Exploration under Uncertainty. [Citation Graph (, )][DBLP]


  22. A policy gradient method for SMDPs with application to call admission control. [Citation Graph (, )][DBLP]


  23. A Bayesian exploration-exploitation approach for optimal online sensing and planning with a visually guided mobile robot. [Citation Graph (, )][DBLP]


  24. A boosting approach to structure learning of graphs with and without prior knowledge. [Citation Graph (, )][DBLP]


  25. Channel Tracking for Relay Networks via Adaptive Particle MCMC [Citation Graph (, )][DBLP]


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