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ORCIDNicolas Chopin
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2020 – today
- 2024
[j11]Nicolas Chopin, Mathieu Gerber
:
Higher-Order Monte Carlo through Cubic Stratification. SIAM J. Numer. Anal. 62(1): 229-247 (2024)- [c9]Nicolas Chopin, Francesca R. Crucinio, Anna Korba:
A connection between Tempering and Entropic Mirror Descent. ICML 2024 - [i10]Otmane Sakhi, Imad Aouali, Pierre Alquier, Nicolas Chopin:
Logarithmic Smoothing for Pessimistic Off-Policy Evaluation, Selection and Learning. CoRR abs/2405.14335 (2024) - 2023
- [j10]Otmane Sakhi, David Rohde, Nicolas Chopin:
Fast Slate Policy Optimization: Going Beyond Plackett-Luce. Trans. Mach. Learn. Res. 2023 (2023) - [c8]Nicolas Chopin, Andras Fulop, Jeremy Heng, Alexandre H. Thiery:
Computational Doob h-transforms for Online Filtering of Discretely Observed Diffusions. ICML 2023: 5904-5923 - [c7]Otmane Sakhi, Pierre Alquier, Nicolas Chopin:
PAC-Bayesian Offline Contextual Bandits With Guarantees. ICML 2023: 29777-29799 - [i9]Adrien Corenflos, Matthew Sutton, Nicolas Chopin:
Debiasing Piecewise Deterministic Markov Process samplers using couplings. CoRR abs/2306.15422 (2023) - [i8]Otmane Sakhi, David Rohde, Nicolas Chopin:
Fast Slate Policy Optimization: Going Beyond Plackett-Luce. CoRR abs/2308.01566 (2023) - 2022
- [j9]Adrien Corenflos, Nicolas Chopin, Simo Särkkä:
De-Sequentialized Monte Carlo: a parallel-in-time particle smoother. J. Mach. Learn. Res. 23: 283:1-283:39 (2022) - [i7]Adrien Corenflos, Nicolas Chopin, Simo Särkkä:
De-Sequentialized Monte Carlo: a parallel-in-time particle smoother. CoRR abs/2202.02264 (2022) - [i6]Nicolas Chopin, Andras Fulop, Jeremy Heng, Alexandre H. Thiery:
Computational Doob's h-transforms for Online Filtering of Discretely Observed Diffusions. CoRR abs/2206.03369 (2022) - [i5]Nicolas Chopin, Mathieu Gerber:
Higher-order stochastic integration through cubic stratification. CoRR abs/2210.01554 (2022) - [i4]Otmane Sakhi, Nicolas Chopin, Pierre Alquier:
PAC-Bayesian Offline Contextual Bandits With Guarantees. CoRR abs/2210.13132 (2022) - 2021
- [j8]Nicolas Chopin, Gabriel Ducrocq:
Fast Compression of MCMC Output. Entropy 23(8): 1017 (2021) - [c6]Nicolas Chopin, Mike Gartrell, Dawen Liang, Alberto Lumbreras, David Rohde, Yixin Wang:
Bayesian Causal Inference for Real World Interactive Systems. KDD 2021: 4114-4115
2010 – 2019
- 2017
- [c5]Shravan Vasishth, Nicolas Chopin, Robin J. Ryder, Bruno Nicenboim:
Modelling dependency completion in sentence comprehension as a Bayesian hierarchical mixture process: A case study involving Chinese relative clauses. CogSci 2017 - [i3]Shravan Vasishth, Nicolas Chopin, Robin J. Ryder, Bruno Nicenboim:
Modelling dependency completion in sentence comprehension as a Bayesian hierarchical mixture process: A case study involving Chinese relative clauses. CoRR abs/1702.00564 (2017) - 2016
- [j7]Pierre Alquier, James Ridgway, Nicolas Chopin:
On the properties of variational approximations of Gibbs posteriors. J. Mach. Learn. Res. 17: 239:1-239:41 (2016) - 2015
- [j6]Simon Barthelmé, Nicolas Chopin:
The Poisson transform for unnormalised statistical models. Stat. Comput. 25(4): 767-780 (2015) - [c4]Nicolas Chopin, Mathieu Gerber:
Application of sequential Quasi-Monte Carlo to autonomous positioning. EUSIPCO 2015: 489-493 - 2014
- [c3]Colas Schretter, Zhijian He, Mathieu Gerber, Nicolas Chopin, Harald Niederreiter:
Van der Corput and Golden Ratio Sequences Along the Hilbert Space-Filling Curve. MCQMC 2014: 531-544 - [c2]James Ridgway, Pierre Alquier, Nicolas Chopin, Feng Liang:
PAC-Bayesian AUC classification and scoring. NIPS 2014: 658-666 - 2013
- [j5]Christian Schäfer, Nicolas Chopin:
Sequential Monte Carlo on large binary sampling spaces. Stat. Comput. 23(2): 163-184 (2013) - [j4]Sumeetpal S. Singh, Nicolas Chopin, Nick Whiteley:
Bayesian Learning of Noisy Markov Decision Processes. ACM Trans. Model. Comput. Simul. 23(1): 4:1-4:25 (2013) - 2012
- [j3]Nicolas Chopin, Tony Lelièvre, Gabriel Stoltz:
Free energy methods for Bayesian inference: efficient exploration of univariate Gaussian mixture posteriors. Stat. Comput. 22(4): 897-916 (2012) - [i2]Nicolas Chopin, Andrew Gelman, Kerrie L. Mengersen, Christian P. Robert:
In praise of the referee. CoRR abs/1205.4304 (2012) - [i1]Sumeetpal S. Singh, Nicolas Chopin, Nick Whiteley:
Bayesian learning of noisy Markov decision processes. CoRR abs/1211.5901 (2012) - 2011
- [j2]Nicolas Chopin:
Fast simulation of truncated Gaussian distributions. Stat. Comput. 21(2): 275-288 (2011) - [c1]Simon Barthelmé, Nicolas Chopin:
ABC-EP: Expectation Propagation for Likelihoodfree Bayesian Computation. ICML 2011: 289-296
2000 – 2009
- 2009
- [j1]Nicolas Chopin:
Jim Albert: Bayesian computation with R. Stat. Comput. 19(1): 111-112 (2009)
Coauthor Index
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