Clara Grazian
Title
Cited by
Cited by
Year
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
362019
Validating a 14-drug microtiter plate containing bedaquiline and delamanid for large-scale research susceptibility testing of Mycobacterium tuberculosis
PMV Rancoita, F Cugnata, AL Gibertoni Cruz, E Borroni, SJ Hoosdally, ...
Antimicrobial agents and chemotherapy 62 (9), e00344-18, 2018
352018
Accelerating Metropolis-Hastings algorithms by delayed acceptance
M Banterle, C Grazian, A Lee, CP Robert
arXiv preprint arXiv:1503.00996, 2015
302015
Accelerating Metropolis-Hastings algorithms by delayed acceptance
M Banterle, C Grazian, A Lee, CP Robert
Foundations of Data Science 1 (2), 103, 2019
202019
Approximating the Likelihood in ABC
CC Drovandi, C Grazian, K Mengersen, C Robert
Handbook of approximate bayesian computation, 321-368, 2018
182018
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
15*2019
Approximate Bayesian inference in semiparametric copula models
C Grazian, B Liseo
Bayesian Analysis 12 (4), 991-1016, 2017
152017
GenomegaMap: within-species genome-wide d_N/d_S estimation from over 10,000 genomes
Molecular Biology and Evolution, 2020
112020
GenomegaMap: within-species genome-wide d_N/d_S estimation from over 10,000 genomes
Molecular Biology and Evolution, 2020
11*2020
Jeffreys’ priors for mixture estimation
C Grazian, CP Robert
Bayesian statistics from methods to models and applications, 37-48, 2015
112015
Accelerating Metropolis-Hastings algorithms: Delayed acceptance with prefetching
M Banterle, C Grazian, CP Robert
arXiv preprint arXiv:1406.2660, 2014
102014
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
92018
Jeffreys priors for mixture estimation: Properties and alternatives
C Grazian, CP Robert
Computational Statistics & Data Analysis 121, 149-163, 2018
82018
Approximate integrated likelihood via ABC methods
C Grazian, B Liseo
Statistics and its interface 8 (2), 161-171, 2015
82015
Approximate Bayesian computation for copula estimation
C Grazian, B Liseo
Statistica 75 (1), 111-127, 2015
72015
A review of approximate Bayesian computation methods via density estimation: Inference for simulator‐models
C Grazian, Y Fan
Wiley Interdisciplinary Reviews: Computational Statistics 12 (4), e1486, 2020
52020
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
52020
Reconstruction of dispersal patterns of hypervirulent meningococcal strains of serogroup C: cc11 by phylogenomic time trees
A Lo Presti, A Neri, C Fazio, P Vacca, L Ambrosio, C Grazian, B Liseo, ...
Journal of clinical microbiology 58 (1), e01351-19, 2019
52019
New formulation of the logistic-Gaussian process to analyze trajectory tracking data
G Mastrantonio, C Grazian, S Mancinelli, E Bibbona
The Annals of Applied Statistics 13 (4), 2483-2508, 2019
22019
Estimating MIC distributions and cutoffs through mixture models: an application to establish M. Tuberculosis resistance
C Grazian
bioRxiv, 643429, 2019
22019
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Articles 1–20