Study the galaxy distribution characterisation via {Bayesian} statistical learning of spatial marked point processes.

@inproceedings{gillot_study_RM2023,
 abstract = {Marked point process and Bayesian inference are powerful tools for analysing spatial data. Here the work done by Hurtado Gil et al. (2021) is analysed and a new in-homogeneous with superposed interaction is proposed. The results indicate a correct fit of the model and allow the study of the significance of the parameter at the corresponding pre-fixed interaction ranges. To this work in progress, immediate conclusions and perspectives are outlined.},
 author = {Gillot, Nathan and Stoica, Radu Stefan and Gemmerle, Didier},
 booktitle = {2023 {RING} meeting},
 language = {en},
 pages = {8},
 publisher = {ASGA},
 title = {Study the galaxy distribution characterisation via {Bayesian} statistical learning of spatial marked point processes.},
 year = {2023}
}