L. Alamichel, D. Bystrova, J. Arbel and G. Kon Kam King, “Bayesian mixture models (in)consistency for the number of clusters”. Accepted in the Scandinavian Journal of Statistics, 2024. (arxiv/HAL)
C. Lawless, L. Alamichel, J. Arbel and G. Kon Kam King, “Clustering inconsistency for Pitman–Yor mixture models with a prior on the precision but fixed discount parameter”, In Fifth Symposium on Advances in Approximate Bayesian Inference, 2023. (Link)
L. Alamichel, J. Arbel, G. Kon Kam King and I. Prünster, “Species Sensitivity Distribution revisited: a Bayesian nonparametric approach”, Submitted, 2024.
Conferences
2024
BAYSM 2024, Poster: “Bayesian mixture models (in)consistency for the number of clusters” (Link)
ISBA 2024, Poster: “Bayesian mixture models (in)consistency for the number of clusters” (Link), Best poster award
Approximation Methods in Bayesian Analysis Workshop, Poster: “Bayesian mixture models (in)consistency for the number of clusters”
AABI 2023, Communication & Poster: “Clustering inconsistency for Pitman–Yor mixture models with a prior on the precision but fixed discount parameter” (Link)
Bayes@CIRM, Poster: “Bayesian mixture models (in)consistency for the number of clusters” (Link)
CMStatistics 2023, Invited Talk “Bayesian mixture models (in)consistency for the number of clusters” (Link)
2022
JDS 2022, Communication & Contributed Talk: “On the consistency of Bayesian nonparametric mixtures for the number of clusters” (Link)
BAYSM 2022, Poster: “Bayesian nonparametric mixtures inconsistency for the number of clusters” (Link)
ISBA 2022, Contributed Talk: “On the consistency of Bayesian nonparametric mixtures for the number of clusters” (Link)
BNP13, Poster: “Bayesian mixture models (in)consistency for the number of clusters” (Link)