Our Department

Department Alumni Fest 2016

Subscribe to email list

Please select the email list(s) to which you wish to subscribe.

Publications by Alexandre Bouchard-Côté

2017

Zhai Y, Bouchard-Côté A. A Poissonian model of indel rate variation for phylogenetic tree inference. Systematic Biology. 2017;(Accepted).
Bouchard-Côté A, Vollmer SJ, Doucet A. The Bouncy Particle Sampler: A non-reversible rejection-free Markov chain Monte Carlo method. Journal of the American Statistical Association. 2017;(Accepted).
Salehi S, Steif A, Roth A, Aparicio S, Bouchard-Côté A, Shah SP. ddClone: joint statistical inference of clonal populations from single-cell and bulk tumor sequencing data. Genome Biology. 2017;(Accepted).
Jun S-H, Bouchard-Côté A. Sequential Graph Matching with Sequential Monte Carlo. In AISTATS. 2017.

2016

Zhai Y, Bouchard-Côté A. Inferring history of human populations using single-nucleotide polymorphism. Annals of Applied Stat. 2016;10:2047–2074.
Shahriari B, Bouchard-Côté A, de Freitas N. Unbounded Bayesian optimization via regularization. In AISTATS. 2016. pp. 1168–1176.
Roth A, McPherson A, Laks E, Biele J, Yap D, Wan A, et al. Clonal genotype and population structure inference from single-cell tumor sequencing. Nature Methods. 2016;13:575–576.
Lindsten F, Johansen AM, Naesseth CA, Kirkpatrick B, Schon TB, Aston J, et al. Divide-and-conquer with sequential Monte Carlo. Journal of Computational Statistics and Graphics. 2016;(In Press).

2015

Jewell S, Spencer N, Bouchard-Côté A. Atomic spatial processes. In International Conference on Machine Learning (ICML). 2015. pp. 248–256.
Bouchard-Côté A, Doucet A, Roth A. Particle Gibbs split-merge sampling for Bayesian inference in mixture models. Journal of Machine Learning Research. 2015;(Accepted).
Zhao T, Cumberworth A, Wang Z, Gsponer J, de Freitas N, Bouchard-Côté A. Bayesian analysis of continuous time Markov chains with application to phylogenetic modelling. Bayesian Analysis. 2015;11:1203–1237.
Wang L, Bouchard-Côté A, Doucet A. Bayesian phylogenetic inference using the combinatorial sequential Monte Carlo method. Journal of the American Statistical Association. 2015;110:1362–1374.

2014

Hajiaghayi M, Kirkpatrick B, Wang L, Bouchard-Côté A. Efficient continuous-time Markov chain estimation. In International Conference on Machine Learning (ICML). 2014. pp. 638–646.
Roth A, Khattra J, Yap D, Wan A, Laks E, Biele J, et al. PyClone: statistical inference of clonal population structure in cancer. Nature Methods. 2014;11:396–398.
Bouchard-Côté A. Sequential Monte Carlo (SMC) for Bayesian phylogenetics. In: Chen M-H, Kuo L, Lewis PO (eds.). Bayesian phylogenetics: methods, algorithms, and applications. 2014. pp. 163–186.
Jun S-H, Bouchard-Côté A. Memory (and time) efficient sequential Monte Carlo. In International Conference on Machine Learning (ICML). 2014. pp. 514–522.

2013

Bouchard-Côté A, Jordan MI. Evolutionary inference via the Poisson indel process. Proceedings of the National Academy of Sciences. 2013;110:1160–1166.
Bouchard-Côté A, Hall D, Griffiths TL, Klein D. Automated reconstruction of ancient languages using probabilistic models of sound change. Proceedings of the National Academy of Sciences. 2013;110:4224–4229.
Bouchard-Côté A. A note on probabilistic models over strings: the linear algebra approach. Bulletin of Mathematical Biology. 2013;75:2529–2550.

2012

Jun S-H, Wang L, Bouchard-Côté A. Entangled Monte Carlo. In Advances in Neural Information Processing Systems 25 (NIPS). 2012. pp. 2735–2743.
Bouchard-Côté A, Sankararaman S, Jordan MI. Phylogenetic inference via sequential Monte Carlo. Systematic Biology. 2012;61:579–593.
Bouchard-Côté A, Kirkpatrick B. Bayesian pedigree analysis using measure factorization. In Advances in Neural Information Processing Systems 25 (NIPS). 2012. pp. 2906–2914.

2011

Saeedi A, Bouchard-Côté A. Priors over recurrent continuous time processes. In Advances in Neural Information Processing Systems 24 (NIPS). 2011. pp. 2052–2060.

2010

Berg-Kirkpatrick T, Bouchard-Côté A, DeNero J, Klein D. Painless unsupervised learning with features. In Proceedings of the North American Chapter of the Association for Computational Linguistics (NAACL10). 2010. pp. 582–590.
Bouchard-Côté A, Jordan MI. Variational inference over combinatorial spaces. In Advances in Neural Information Processing Systems 23 (NIPS). 2010. pp. 280–288.

2009

Bouchard-Côté A, Griffiths TL, Klein D. Improved reconstruction of protolanguage word forms. In Proceedings of the North American Chapter of the Association for Computational Linguistics (NAACL09). 2009. pp. 65–73.
Bouchard-Côté A, Jordan MI. Optimization of structured mean field objectives. In Proceedings of the 25th Conference on Uncertainty in Artificial Intelligence (UAI09). 2009. pp. 67–74.
Bouchard-Côté A, Petrov S, Klein D. Randomized pruning: efficiently calculating expectations in large dynamic programs. In Advances in Neural Information Processing Systems 22 (NIPS). 2009. pp. 144–152.

2008

DeNero J, Bouchard-Côté A, Klein D. Sampling alignment structure under a Bayesian translation model. In Proceedings of the 2008 Conference on Empirical Methods on Natural Language Processing (EMNLP08). 2008. pp. 314–323.
Bouchard-Côté A, Jordan MI, Klein D. Efficient inference in phylogenetic InDel trees. In Advances in Neural Information Processing Systems 21 (NIPS). 2008. pp. 177–184.

2007

Bouchard-Côté A, Liang P, Griffiths T, Klein D. A probabilistic approach to diachronic phonology. In Proceedings of the 2007 Conference on Empirical Methods on Natural Language Processing (EMNLP07). 2007. pp. 887–896.
Bouchard-Côté A, Liang P, Griffiths T, Klein D. A probabilistic approach to language change. In Advances in Neural Information Processing Systems 20 (NIPS). 2007.

2006

Liang P, Bouchard-Côté A, Klein D, Taskar B. An end-to-end discriminative approach to machine translation. In Proceedings of the 44th Annual Meeting of the Association for Computational Linguistics (ACL06). 2006. pp. 761–768.

2005

Bouchard-Côté A, Ferns N, Panangaden P, Precup D. An approximation algorithm for labelled Markov processes: towards realistic approximation. In Proceedings of the International Conference on Quantitative Evaluation of Systems. 2005. pp. 54–62.