Arnaud Doucet

2009
28	EE	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
27	EE	Francois Caron, Arnaud Doucet: Sparse Bayesian nonparametric regression. ICML 2008: 88-95
26	EE	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)
25	EE	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)
24	EE	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
23	EE	Matthew Hoffman, Arnaud Doucet, Nando de Freitas, Ajay Jasra: Bayesian Policy Learning with Trans-Dimensional MCMC. NIPS 2007
22	EE	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
21	EE	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)
20	EE	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)
19	EE	Simon I. Hill, Arnaud Doucet: A Framework for Kernel-Based Multi-Category Classification. J. Artif. Intell. Res. (JAIR) 30: 525-564 (2007)
2006
18	EE	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
17	EE	Simon I. Hill, Arnaud Doucet: Adapting two-class support vector classification methods to many class problems. ICML 2005: 313-320
16	EE	Mike Klaas, Nando de Freitas, Arnaud Doucet: Toward Practical N2 Monte Carlo: the Marginal Particle Filter. UAI 2005: 308-315
2003
15	EE	Jaco Vermaak, Arnaud Doucet, Patrick Pérez: Maintaining Multi-Modality through Mixture Tracking. ICCV 2003: 1110-1116
14	EE	Jaco Vermaak, Simon J. Godsill, Arnaud Doucet: Sequential Bayesian Kernel Regression. NIPS 2003
13		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
12	EE	Sumetpal Singh, Vladislav Tadic, Arnaud Doucet: A policy gradient method for SMDPs with application to call admission control. ICARCV 2002: 1268-1274
11		Shien-Shin Tham, Arnaud Doucet, Kotagiri Ramamohanarao: Sparse Bayesian Learning for Regression and Classification using Markov Chain Monte Carlo. ICML 2002: 634-641
10	EE	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
9	EE	Christophe Andrieu, Nando de Freitas, Arnaud Doucet: Rao-Blackwellised Particle Filtering via Data Augmentation. NIPS 2001: 561-567
8	EE	Christophe Andrieu, Nando de Freitas, Arnaud Doucet: Robust Full Bayesian Learning for Radial Basis Networks. Neural Computation 13(10): 2359-2407 (2001)
2000
7		Rudolph van der Merwe, Arnaud Doucet, Nando de Freitas, Eric A. Wan: The Unscented Particle Filter. NIPS 2000: 584-590
6	EE	Christophe Andrieu, Nando de Freitas, Arnaud Doucet: Reversible Jump MCMC Simulated Annealing for Neural Networks. UAI 2000: 11-18
5	EE	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	EE	Christophe Andrieu, João F. G. de Freitas, Arnaud Doucet: Robust Full Bayesian Methods for Neural Networks. NIPS 1999: 379-385
1998
1	EE	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

Coauthor Index

1	Christophe Andrieu	[2] [4] [6] [8] [9] [13]
2	Shovan Bhaumik	[28]
3	Mark Briers	[18]
4	Francois Caron	[25] [27]
5	José A. Castellanos	[22]
6	Manuel Davy	[24] [25]
7	Emmanuel Duflos	[25]
8	Robin J. Evans	[21]
9	João F. G. de Freitas	[1] [2] [3]
10	Nando de Freitas	[5] [6] [7] [8] [9] [13] [16] [18] [22] [23]
11	Andrew H. Gee	[1] [3]
12	T. K. Ghoshal	[28]
13	Simon J. Godsill	[10] [14]
14	Simon I. Hill	[17] [19]
15	Matthew Hoffman	[23]
16	Christopher C. Holmes	[26]
17	Ajay Jasra	[23] [26]
18	Adam M. Johansen	[24]
19	Michael I. Jordan	[13]
20	Nikolaos Kantas	[21]
21	Mike Klaas	[16] [18]
22	Dustin Lang	[18]
23	Ruben Martinez-Cantin	[22]
24	Simon Maskell	[18]
25	Rudolph van der Merwe	[7]
26	Kevin P. Murphy	[5]
27	Mahesan Niranjan	[1] [3]
28	Patrick Pérez	[15]
29	Kotagiri Ramamohanarao	[11]
30	Christian P. Robert	[10]
31	Stuart J. Russell	[5]
32	Smita Sadhu	[28]
33	Sumeetpal S. Singh	[20] [21]
34	Sumetpal Singh	[12]
35	David A. Stephens	[26]
36	Vladislav Tadic	[12]
37	Vladislav B. Tadic	[20]
38	Shien-Shin Tham	[11]
39	Philippe Vanheeghe	[25]
40	Jaco Vermaak	[14] [15]
41	Ba-Ngu Vo	[21]
42	Eric A. Wan	[7]

Colors in the list of coauthors