Clara Grazian
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Accelerating Metropolis-Hastings algorithms by delayed acceptance
M Banterle, C Grazian, A Lee, CP Robert
arXiv preprint arXiv:1503.00996, 2015
Validating a 14-drug microtiter plate containing bedaquiline and delamanid for large-scale research susceptibility testing of Mycobacterium tuberculosis
PMV Rancoita, F Cugnata, ALG Cruz, E Borroni, SJ Hoosdally, TM Walker, ...
Antimicrobial agents and chemotherapy 62 (9), e00344-18, 2018
Jeffreys’ priors for mixture estimation
C Grazian, CP Robert
Bayesian statistics from methods to models and applications, 37-48, 2015
Approximating the likelihood in abc
CC Drovandi, C Grazian, K Mengersen, C Robert
Handbook of Approximate Bayesian Computation, 321-368, 2018
Approximate Bayesian inference in semiparametric copula models
C Grazian, B Liseo
Bayesian Analysis 12 (4), 991-1016, 2017
Accelerating Metropolis-Hastings algorithms: Delayed acceptance with prefetching
M Banterle, C Grazian, CP Robert
arXiv preprint arXiv:1406.2660, 2014
Approximate integrated likelihood via ABC methods
C Grazian, B Liseo
Statistics and its interface 8 (2), 161-171, 2015
Jeffreys priors for mixture estimation: Properties and alternatives
C Grazian, CP Robert
Computational Statistics & Data Analysis 121, 149-163, 2018
Application of machine learning techniques to tuberculosis drug resistance analysis
DACCC Samaneh Kouchaki, Yang Yang, T Walker, A Sarah Walker, Daniel J Wilson ...
Bioinformatics 35 (13), 2276-2282, 2019
Approximate Bayesian computation for copula estimation
C Grazian, B Liseo
Statistica 75 (1), 111-127, 2015
Bayesian analysis
SC Wang
Interdisciplinary Computing in Java Programming, 195-210, 2003
DeepAMR for predicting co-occurrent resistance of Mycobacterium tuberculosis
DAC Yang Yang, Timothy M Walker, A Sarah Walker, Daniel J Wilson, Timothy E ...
Bioinformatics, 1-10, 2019
Automated detection of bacterial growth on 96-well plates for high-throughput drug susceptibility testing of Mycobacterium tuberculosis
PW Fowler, ALG Cruz, SJ Hoosdally, L Jarrett, E Borroni, ...
Microbiology 165 (5), 585-585, 2018
On a loss-based prior for the number of components in mixture models
C Grazian, C Villa, B Liseo
Statistics & Probability Letters 158, 108656, 2020
A review of approximate Bayesian computation methods via density estimation: Inference for simulator‐models
C Grazian, Y Fan
Wiley Interdisciplinary Reviews: Computational Statistics, e1486, 2019
Accelerating Metropolis-Hastings algorithms by delayed acceptance
M Banterle, C Grazian, A Lee, CP Robert
Foundations of Data Science 1 (2), 103-128, 2019
Deep Fundamental Factor Models
MF Dixon, NG Polson
arXiv preprint arXiv:1903.07677, 2019
Modelling preference data with the Wallenius distribution
C Grazian, F Leisen, B Liseo
Journal of the Royal Statistical Society: Series A (Statistics in Society …, 2019
Bayesian mixture models: Theory and methods
J Rousseau, J., Grazian, C. and Lee
Handbook of Mixture Analysis, 2019
Approximate Bayesian Methods for Multivariate and Conditional Copulae
C Grazian, B Liseo
International Conference on Soft Methods in Probability and Statistics, 261-268, 2016
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