| 2009 | ||
|---|---|---|
| 31 | Hendrik Kück, Matthew Hoffman, Arnaud Doucet, Nando de Freitas: Inference and Learning for Active Sensing, Experimental Design and Control. IbPRIA 2009: 1-10 | |
| 30 | Smita Sadhu, Shovan Bhaumik, Arnaud Doucet, T. K. Ghoshal: Particle-method-based formulation of risk-sensitive filter. Signal Processing 89(3): 314-319 (2009) | |
| 2008 | ||
| 29 | Francois Caron, Arnaud Doucet: Sparse Bayesian nonparametric regression. ICML 2008: 88-95 | |
| 28 | Ajay Jasra, Arnaud Doucet, David A. Stephens, Christopher C. Holmes: Interacting sequential Monte Carlo samplers for trans-dimensional simulation. Computational Statistics & Data Analysis 52(4): 1765-1791 (2008) | |
| 27 | Francois Caron, Manuel Davy, Arnaud Doucet, Emmanuel Duflos, Philippe Vanheeghe: Bayesian Inference for Linear Dynamic Models With Dirichlet Process Mixtures. IEEE Transactions on Signal Processing 56(1): 71-84 (2008) | |
| 26 | Adam M. Johansen, Arnaud Doucet, Manuel Davy: Particle methods for maximum likelihood estimation in latent variable models. Statistics and Computing 18(1): 47-57 (2008) | |
| 2007 | ||
| 25 | Matthew Hoffman, Arnaud Doucet, Nando de Freitas, Ajay Jasra: Bayesian Policy Learning with Trans-Dimensional MCMC. NIPS 2007 | |
| 24 | Ruben Martinez-Cantin, Nando de Freitas, Arnaud Doucet, José A. Castellanos: Active Policy Learning for Robot Planning and Exploration under Uncertainty. Robotics: Science and Systems 2007 | |
| 23 | Sumeetpal S. Singh, Nikolaos Kantas, Ba-Ngu Vo, Arnaud Doucet, Robin J. Evans: Simulation-based optimal sensor scheduling with application to observer trajectory planning. Automatica 43(5): 817-830 (2007) | |
| 22 | Sumeetpal S. Singh, Vladislav B. Tadic, Arnaud Doucet: A policy gradient method for semi-Markov decision processes with application to call admission control. European Journal of Operational Research 178(3): 808-818 (2007) | |
| 21 | Simon I. Hill, Arnaud Doucet: A Framework for Kernel-Based Multi-Category Classification. J. Artif. Intell. Res. (JAIR) 30: 525-564 (2007) | |
| 2006 | ||
| 20 | Mike Klaas, Mark Briers, Nando de Freitas, Arnaud Doucet, Simon Maskell, Dustin Lang: Fast particle smoothing: if I had a million particles. ICML 2006: 481-488 | |
| 2005 | ||
| 19 | Simon I. Hill, Arnaud Doucet: Adapting two-class support vector classification methods to many class problems. ICML 2005: 313-320 | |
| 18 | Mike Klaas, Nando de Freitas, Arnaud Doucet: Toward Practical N2 Monte Carlo: the Marginal Particle Filter. UAI 2005: 308-315 | |
| 2003 | ||
| 17 | Jaco Vermaak, Arnaud Doucet, Patrick Pérez: Maintaining Multi-Modality through Mixture Tracking. ICCV 2003: 1110-1116 | |
| 16 | Jaco Vermaak, Simon J. Godsill, Arnaud Doucet: Sequential Bayesian Kernel Regression. NIPS 2003 | |
| 15 | Christophe Andrieu, Nando de Freitas, Arnaud Doucet, Michael I. Jordan: An Introduction to MCMC for Machine Learning. Machine Learning 50(1-2): 5-43 (2003) | |
| 2002 | ||
| 14 | Sumetpal Singh, Vladislav Tadic, Arnaud Doucet: A policy gradient method for SMDPs with application to call admission control. ICARCV 2002: 1268-1274 | |
| 13 | Shien-Shin Tham, Arnaud Doucet, Kotagiri Ramamohanarao: Sparse Bayesian Learning for Regression and Classification using Markov Chain Monte Carlo. ICML 2002: 634-641 | |
| 12 | Jaco Vermaak, Christophe Andrieu, Arnaud Doucet, Simon J. Godsill: Particle methods for Bayesian modeling and enhancement of speech signals. IEEE Transactions on Speech and Audio Processing 10(3): 173-185 (2002) | |
| 11 | Arnaud Doucet, Simon J. Godsill, Christian P. Robert: Marginal maximum a posteriori estimation using Markov chain Monte Carlo. Statistics and Computing 12(1): 77-84 (2002) | |
| 2001 | ||
| 10 | Christophe Andrieu, Nando de Freitas, Arnaud Doucet: Rao-Blackwellised Particle Filtering via Data Augmentation. NIPS 2001: 561-567 | |
| 9 | Christophe Andrieu, Nando de Freitas, Arnaud Doucet: Robust Full Bayesian Learning for Radial Basis Networks. Neural Computation 13(10): 2359-2407 (2001) | |
| 8 | Christophe Andrieu, Petar M. Djuric, Arnaud Doucet: Model selection by MCMC computation. Signal Processing 81(1): 19-37 (2001) | |
| 2000 | ||
| 7 | Rudolph van der Merwe, Arnaud Doucet, Nando de Freitas, Eric A. Wan: The Unscented Particle Filter. NIPS 2000: 584-590 | |
| 6 | Christophe Andrieu, Nando de Freitas, Arnaud Doucet: Reversible Jump MCMC Simulated Annealing for Neural Networks. UAI 2000: 11-18 | |
| 5 | Arnaud Doucet, Nando de Freitas, Kevin P. Murphy, Stuart J. Russell: Rao-Blackwellised Particle Filtering for Dynamic Bayesian Networks. UAI 2000: 176-183 | |
| 4 | Christophe Andrieu, Arnaud Doucet: Simulated annealing for maximum a Posteriori parameter estimation of hidden Markov models. IEEE Transactions on Information Theory 46(3): 994-1004 (2000) | |
| 3 | João F. G. de Freitas, Mahesan Niranjan, Andrew H. Gee, Arnaud Doucet: Sequential Monte Carlo Methods to Train Neural Network Models. Neural Computation 12(4): 955-993 (2000) | |
| 1999 | ||
| 2 | Christophe Andrieu, João F. G. de Freitas, Arnaud Doucet: Robust Full Bayesian Methods for Neural Networks. NIPS 1999: 379-385 | |
| 1998 | ||
| 1 | João F. G. de Freitas, Mahesan Niranjan, Arnaud Doucet, Andrew H. Gee: Global Optimisation of Neural Network Models via Sequential Sampling. NIPS 1998: 410-416 | |