Computational Bayesian Statistics Journal Club

Lead: Mariano Gabitto, Flatiron Institute

Topic: The discussion will focus on:

• Antonietta Mira, Reza Solgi, and Daniele Imparato. 2013. Zero variance Markov chain Monte Carlo for Bayesian estimators. Statistical Computing. https://link.springer.com/content/pdf/10.1007/s11222-012-9344-6.pdf

 
 
Please reference the following papers for a more advanced reading in the same approach.
 

• L.F. South, C. J. Oates, A. Mira, and C. Drovandi. 2020. Regularised Zero-Variance Control Variates for High-Dimensional Variance Reduction. arXiv. https://arxiv.org/pdf/1811.05073.pdf

 

• Theodore Papamarkou, Antonietta Mira, and Mark Girolami. 2014. Zero Variance Differential Geometric Markov Chain Monte Carlo Algorithms. Bayesian Analysis. https://projecteuclid.org/download/pdfview_1/euclid.ba/1393251772

 

• Leah F. South, Toni Karvonen, Chris Nemeth, Mark Girolami, Chris. J. Oates, 2020. Semi-Exact Control Functionals From Sard’s Method. arXiv. https://arxiv.org/pdf/2002.00033.pdf

Please email Sara Mejias Gonzalez at [email protected] for Zoom information if you would like to participate.