Nicolas Chopin

According to our database, Nicolas Chopin authored at least 25 papers between 2009 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Higher-Order Monte Carlo through Cubic Stratification.

Nicolas Chopin, Mathieu Gerber

SIAM J. Numer. Anal., February, 2024

Logarithmic Smoothing for Pessimistic Off-Policy Evaluation, Selection and Learning.

Otmane Sakhi, Imad Aouali, Pierre Alquier, Nicolas Chopin

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

A connection between Tempering and Entropic Mirror Descent.

Nicolas Chopin, Francesca R. Crucinio, Anna Korba

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

Fast Slate Policy Optimization: Going Beyond Plackett-Luce.

Otmane Sakhi, David Rohde, Nicolas Chopin

Trans. Mach. Learn. Res., 2023

Debiasing Piecewise Deterministic Markov Process samplers using couplings.

Adrien Corenflos, Matthew Sutton, Nicolas Chopin

CoRR, 2023

PAC-Bayesian Offline Contextual Bandits With Guarantees.

Otmane Sakhi, Pierre Alquier, Nicolas Chopin

Proceedings of the International Conference on Machine Learning, 2023

Computational Doob h-transforms for Online Filtering of Discretely Observed Diffusions.

Nicolas Chopin, Andras Fulop, Jeremy Heng, Alexandre H. Thiery

Proceedings of the International Conference on Machine Learning, 2023

2022

De-Sequentialized Monte Carlo: a parallel-in-time particle smoother.

Adrien Corenflos, Nicolas Chopin, Simo Särkkä

J. Mach. Learn. Res., 2022

Higher-order stochastic integration through cubic stratification.

Nicolas Chopin, Mathieu Gerber

CoRR, 2022

Computational Doob's h-transforms for Online Filtering of Discretely Observed Diffusions.

Nicolas Chopin, Andras Fulop, Jeremy Heng, Alexandre H. Thiery

CoRR, 2022

2021

Fast Compression of MCMC Output.

Nicolas Chopin, Gabriel Ducrocq

Entropy, 2021

Bayesian Causal Inference for Real World Interactive Systems.

Nicolas Chopin, Mike Gartrell, Dawen Liang, Alberto Lumbreras, David Rohde, Yixin Wang

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

2017

Modelling dependency completion in sentence comprehension as a Bayesian hierarchical mixture process: A case study involving Chinese relative clauses.

Shravan Vasishth, Nicolas Chopin, Robin J. Ryder, Bruno Nicenboim

Proceedings of the 39th Annual Meeting of the Cognitive Science Society, 2017

2016

On the properties of variational approximations of Gibbs posteriors.

Pierre Alquier, James Ridgway, Nicolas Chopin

J. Mach. Learn. Res., 2016

2015

The Poisson transform for unnormalised statistical models.

Simon Barthelmé, Nicolas Chopin

Stat. Comput., 2015

Application of sequential Quasi-Monte Carlo to autonomous positioning.

Nicolas Chopin, Mathieu Gerber

Proceedings of the 23rd European Signal Processing Conference, 2015

2014

PAC-Bayesian AUC classification and scoring.

James Ridgway, Pierre Alquier, Nicolas Chopin, Feng Liang

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Van der Corput and Golden Ratio Sequences Along the Hilbert Space-Filling Curve.

Colas Schretter, Zhijian He, Mathieu Gerber, Nicolas Chopin, Harald Niederreiter

Proceedings of the Monte Carlo and Quasi-Monte Carlo Methods, 2014

2013

Bayesian Learning of Noisy Markov Decision Processes.

Sumeetpal S. Singh, Nicolas Chopin, Nick Whiteley

ACM Trans. Model. Comput. Simul., 2013

Sequential Monte Carlo on large binary sampling spaces.

Christian Schäfer, Nicolas Chopin

Stat. Comput., 2013

2012

Free energy methods for Bayesian inference: efficient exploration of univariate Gaussian mixture posteriors.

Nicolas Chopin, Tony Lelièvre, Gabriel Stoltz

Stat. Comput., 2012

In praise of the referee

Nicolas Chopin, Andrew Gelman, Kerrie L. Mengersen, Christian P. Robert

CoRR, 2012

2011

Fast simulation of truncated Gaussian distributions.

Nicolas Chopin

Stat. Comput., 2011

ABC-EP: Expectation Propagation for Likelihoodfree Bayesian Computation.

Simon Barthelmé, Nicolas Chopin

Proceedings of the 28th International Conference on Machine Learning, 2011

2009

Jim Albert: Bayesian computation with R.

Nicolas Chopin

Stat. Comput., 2009