An approximation algorithm for labelled Markov processes: towards realistic approximation. - Alexandre Bouchard-Côté; Norm Ferns; Prakash Panangaden; Doina Precup (QEST, 2005)

An End-to-End Discriminative Approach to Machine Translation. - Percy Liang; Alexandre Bouchard-Côté; Dan Klein 001; Benjamin Taskar (ACL, 2006)

A Probabilistic Approach to Diachronic Phonology. - Alexandre Bouchard-Côté; Percy Liang; Thomas Griffiths 001; Dan Klein 001 (EMNLP-CoNLL, 2007)

A Probabilistic Approach to Language Change. - Alexandre Bouchard-Côté; Percy Liang; Thomas L. Griffiths 001; Dan Klein 001 (NIPS, 2007)

Sampling Alignment Structure under a Bayesian Translation Model. - John DeNero; Alexandre Bouchard-Côté; Dan Klein 001 (EMNLP, 2008)

Efficient Inference in Phylogenetic InDel Trees. - Alexandre Bouchard-Côté; Michael I. Jordan; Dan Klein 001 (NIPS, 2008)

Improved Reconstruction of Protolanguage Word Forms. - Alexandre Bouchard-Côté; Thomas L. Griffiths 001; Dan Klein 001 (HLT-NAACL, 2009)

Randomized Pruning: Efficiently Calculating Expectations in Large Dynamic Programs. - Alexandre Bouchard-Côté; Slav Petrov; Dan Klein 001 (NIPS, 2009)

Optimization of Structured Mean Field Objectives. - Alexandre Bouchard-Côté; Michael I. Jordan (UAI, 2009)

Painless Unsupervised Learning with Features. - Taylor Berg-Kirkpatrick; Alexandre Bouchard-Côté; John DeNero; Dan Klein 001 (HLT-NAACL, 2010)

Variational Inference over Combinatorial Spaces. - Alexandre Bouchard-Côté; Michael I. Jordan (NIPS, 2010)

Probabilistic Models of Evolution and Language Change. - Alexandre Bouchard-Côté (2010)

Priors over Recurrent Continuous Time Processes. - Ardavan Saeedi; Alexandre Bouchard-Côté (NIPS, 2011)

Entangled Monte Carlo. - Seong-Hwan Jun; Liangliang Wang; Alexandre Bouchard-Côté (NIPS, 2012)

Bayesian Pedigree Analysis using Measure Factorization. - Bonnie Kirkpatrick; Alexandre Bouchard-Côté (NIPS, 2012)

A Note on Probabilistic Models over Strings: Inference and Representation with Indexed Matrices - Alexandre Bouchard-Côté (CoRR, 2013)

Automated reconstruction of ancient languages using probabilistic models of sound change. - Alexandre Bouchard-Côté; David Hall 006; Thomas L. Griffiths 001; Dan Klein 001 (Proc. Natl. Acad. Sci. USA, 2013)

Efficient Continuous-Time Markov Chain Estimation. - Monir Hajiaghayi; Bonnie Kirkpatrick; Liangliang Wang; Alexandre Bouchard-Côté (ICML, 2014)

Memory (and Time) Efficient Sequential Monte Carlo. - Seong-Hwan Jun; Alexandre Bouchard-Côté (ICML, 2014)

An Entropy Search Portfolio for Bayesian Optimization. - Bobak Shahriari; Ziyu Wang 001; Matthew W. Hoffman; Alexandre Bouchard-Côté; Nando de Freitas (CoRR, 2014)

Atomic Spatial Processes. - Sean Jewell; Neil Spencer; Alexandre Bouchard-Côté (ICML, 2015)

Unbounded Bayesian Optimization via Regularization. - Bobak Shahriari; Alexandre Bouchard-Côté; Nando de Freitas (AISTATS, 2016)

Sequential Graph Matching with Sequential Monte Carlo. - Seong-Hwan Jun; Samuel W. K. Wong; James V. Zidek; Alexandre Bouchard-Côté (AISTATS, 2017)

Particle Gibbs Split-Merge Sampling for Bayesian Inference in Mixture Models. - Alexandre Bouchard-Côté; Arnaud Doucet; Andrew Roth (J. Mach. Learn. Res., 2017)

Efficient Parameter Estimation for DNA Kinetics Modeled as Continuous-Time Markov Chains. - Sedigheh Zolaktaf; Frits Dannenberg; Erik Winfree; Alexandre Bouchard-Côté; Mark Schmidt 001; Anne Condon (DNA, 2019)

Scalable Metropolis-Hastings for Exact Bayesian Inference with Large Datasets. - Robert Cornish; Paul Vanetti; Alexandre Bouchard-Côté; George Deligiannidis; Arnaud Doucet (ICML, 2019)

Slice Sampling for General Completely Random Measures. - Peiyuan Zhu; Alexandre Bouchard-Côté; Trevor Campbell (UAI, 2020)

Parallel tempering on optimized paths. - Saifuddin Syed; Vittorio Romaniello; Trevor Campbell; Alexandre Bouchard-Côté (ICML, 2021)

Particle-Gibbs Sampling for Bayesian Feature Allocation Models. - Alexandre Bouchard-Côté; Andrew Roth (J. Mach. Learn. Res., 2021)

Analysis of high-dimensional Continuous Time Markov Chains using the Local Bouncy Particle Sampler. - Tingting Zhao; Alexandre Bouchard-Côté (J. Mach. Learn. Res., 2021)

Parallel Tempering With a Variational Reference. - Nikola Surjanovic; Saifuddin Syed; Alexandre Bouchard-Côté; Trevor Campbell (NeurIPS, 2022)

Blang: Bayesian Declarative Modeling of General Data Structures and Inference via Algorithms Based on Distribution Continua. - Alexandre Bouchard-Côté; Kevin Chern; Davor Cubranic; Sahand Hosseini; Justin Hume; Matteo Lepur; Zihui Ouyang; Giorgio Sgarbi (J. Stat. Softw., 2022)

SpatialSort: a Bayesian model for clustering and cell population annotation of spatial proteomics data. - Eric Lee; Kevin Chern; Michael Nissen; Xuehai Wang; Chris Huang; Anita K. Gandhi; Alexandre Bouchard-Côté; Andrew P. Weng; Andrew Roth (Bioinform., 2023)

Pigeons.jl: Distributed Sampling From Intractable Distributions. - Nikola Surjanovic; Miguel Biron-Lattes; Paul Tiede; Saifuddin Syed; Trevor Campbell; Alexandre Bouchard-Côté (CoRR, 2023)

Pseudo-Marginal Inference for CTMCs on Infinite Spaces via Monotonic Likelihood Approximations. - Miguel Biron-Lattes; Alexandre Bouchard-Côté; Trevor Campbell (J. Comput. Graph. Stat., 2023)

autoMALA: Locally adaptive Metropolis-adjusted Langevin algorithm. - Miguel Biron-Lattes; Nikola Surjanovic; Saifuddin Syed; Trevor Campbell; Alexandre Bouchard-Côté (AISTATS, 2024)

MCMC-driven learning. - Alexandre Bouchard-Côté; Trevor Campbell; Geoff Pleiss; Nikola Surjanovic (CoRR, 2024)

AutoStep: Locally adaptive involutive MCMC. - Tiange Liu; Nikola Surjanovic; Miguel Biron-Lattes; Alexandre Bouchard-Côté; Trevor Campbell (CoRR, 2024)

Is Gibbs sampling faster than Hamiltonian Monte Carlo on GLMs? - Son Luu; Zuheng Xu; Nikola Surjanovic; Miguel Biron-Lattes; Trevor Campbell; Alexandre Bouchard-Côté (AISTATS, 2025)

Variance-Reduced Stochastic Optimization for Efficient Inference of Hidden Markov Models. - Evan Sidrow; Nancy Heckman; Alexandre Bouchard-Côté; Sarah M. E. Fortune; Andrew W. Trites; Marie Auger-Méthé (J. Comput. Graph. Stat., 2025)

Variational phylogenetic inference with products over bipartitions. - Evan Sidrow; Alexandre Bouchard-Côté; Lloyd T. Elliott (CoRR, 2025)

AutoSGD: Automatic Learning Rate Selection for Stochastic Gradient Descent. - Nikola Surjanovic; Alexandre Bouchard-Côté; Trevor Campbell (CoRR, 2025)