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Optimal quantisation of probability measures using maximum mean discrepancy

Nov 03, 2020
Onur Teymur, Jackson Gorham, Marina Riabiz, Chris. J. Oates


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Optimal Quantisation of Probability Measures Using Maximum Mean Discrepancy

Oct 14, 2020
Onur Teymur, Jackson Gorham, Marina Riabiz, Chris. J. Oates


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Scalable Control Variates for Monte Carlo Methods via Stochastic Optimization

Jun 12, 2020
Shijing Si, Chris. J. Oates, Andrew B. Duncan, Lawrence Carin, François-Xavier Briol

* 24 pages, 7 figures 

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Optimal Thinning of MCMC Output

May 08, 2020
Marina Riabiz, Wilson Chen, Jon Cockayne, Pawel Swietach, Steven A. Niederer, Lester Mackey, Chris. J. Oates


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Stein Point Markov Chain Monte Carlo

May 09, 2019
Wilson Ye Chen, Alessandro Barp, François-Xavier Briol, Jackson Gorham, Mark Girolami, Lester Mackey, Chris. J. Oates

* Accepted for ICML 2019 

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Causal Discovery as Semi-Supervised Learning

Aug 01, 2018
Chris. J. Oates, Steven M. Hill, Duncan A. Blythe, Sach Mukherjee


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Probabilistic Integration: A Role in Statistical Computation?

Oct 18, 2017
François-Xavier Briol, Chris. J. Oates, Mark Girolami, Michael A. Osborne, Dino Sejdinovic

* Several improvements suggested by reviewers, including additional experiments on uncertainty quantification properties. Change of title: previously "Probabilistic Integration: A Role for Statisticians in Numerical Analysis?" 

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