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Yves F. Atchadé
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2020 – today
- 2024
- [i6]Yi Sun, Debarghya Mukherjee, Yves F. Atchadé:
On the estimation rate of Bayesian PINN for inverse problems. CoRR abs/2406.14808 (2024) - [i5]Indrajit Kalita, Lucia Vilallonga, Yves F. Atchadé:
Data-driven rainfall prediction at a regional scale: a case study with Ghana. CoRR abs/2410.14062 (2024) - 2023
- [c3]Alexander Lin, Bahareh Tolooshams, Yves F. Atchadé, Demba E. Ba:
Probabilistic Unrolling: Scalable, Inverse-Free Maximum Likelihood Estimation for Latent Gaussian Models. ICML 2023: 21153-21181 - [i4]Alexander Lin, Bahareh Tolooshams, Yves F. Atchadé, Demba E. Ba:
Probabilistic Unrolling: Scalable, Inverse-Free Maximum Likelihood Estimation for Latent Gaussian Models. CoRR abs/2306.03249 (2023) - [i3]Yves F. Atchadé, Xinru Liu, Qiuyun Zhu:
A statistical perspective on algorithm unrolling models for inverse problems. CoRR abs/2311.06395 (2023) - 2021
- [j11]Yves F. Atchadé:
Approximate Spectral Gaps for Markov Chain Mixing Times in High Dimensions. SIAM J. Math. Data Sci. 3(3): 854-872 (2021) - 2020
- [j10]Hossein Keshavarz, George Michailidis, Yves F. Atchadé:
Sequential change-point detection in high-dimensional Gaussian graphical models. J. Mach. Learn. Res. 21: 82:1-82:57 (2020) - [j9]Joonha Park, Yves F. Atchadé:
Markov chain Monte Carlo algorithms with sequential proposals. Stat. Comput. 30(5): 1325-1345 (2020) - [i2]Qiuyun Zhu, Yves F. Atchadé:
On Bayesian sparse canonical correlation analysis via Rayleigh quotient framework. CoRR abs/2010.08627 (2020)
2010 – 2019
- 2019
- [j8]Yves F. Atchadé:
Quasi-Bayesian estimation of large Gaussian graphical models. J. Multivar. Anal. 173: 656-671 (2019) - 2018
- [j7]Leland Bybee, Yves F. Atchadé:
Change-Point Computation for Large Graphical Models: A Scalable Algorithm for Gaussian Graphical Models with Change-Points. J. Mach. Learn. Res. 19: 11:1-11:38 (2018) - [c2]Gersende Fort, Laurent Risser, Yves F. Atchadé, Eric Moulines:
Stochastic Fista Algorithms: So Fast ? SSP 2018: 796-800 - [i1]Hossein Keshavarz, George Michailidis, Yves F. Atchadé:
Sequential change-point detection in high-dimensional Gaussian graphical models. CoRR abs/1806.07870 (2018) - 2017
- [j6]Yves F. Atchadé, Gersende Fort, Eric Moulines:
On Perturbed Proximal Gradient Algorithms. J. Mach. Learn. Res. 18: 10:1-10:33 (2017) - 2015
- [j5]Yves F. Atchadé, Yizao Wang:
On the convergence rates of some adaptive Markov chain Monte Carlo algorithms. J. Appl. Probab. 52(3): 811-825 (2015) - 2014
- [j4]Jing Wang, Yves F. Atchadé:
Approximate Bayesian Computation for Exponential Random Graph Models for Large Social Networks. Commun. Stat. Simul. Comput. 43(2): 359-377 (2014) - 2013
- [j3]Jing Wang, Anocha Aribarg, Yves F. Atchadé:
Modeling Choice Interdependence in a Social Network. Mark. Sci. 32(6): 977-997 (2013) - 2011
- [j2]Yves F. Atchadé:
A computational framework for empirical Bayes inference. Stat. Comput. 21(4): 463-473 (2011) - [j1]Yves F. Atchadé, Gareth O. Roberts, Jeffrey S. Rosenthal:
Towards optimal scaling of metropolis-coupled Markov chain Monte Carlo. Stat. Comput. 21(4): 555-568 (2011)
2000 – 2009
- 2006
- [c1]Christophe Andrieu, Yves F. Atchadé:
On the efficiency of adaptive MCMC algorithms. VALUETOOLS 2006: 43
Coauthor Index
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