Papers (and other useful stuff)
Here you find the short-author papers I contributed to as well as some useful resources.
CV and publications
| Link | Description |
|---|---|
CV | Curriculum Vitae |
Publications | List of publications |
ADS | Complete list of publications on ADS |
Papers
| Link | Description |
|---|---|
Ng et al. (2024) | Inferring cosmology from gravitational waves using non-parametric detector-frame mass distribution |
Poon et al. (2024) | Galaxy lens reconstruction based on strongly lensed gravitational waves: similarity transformation degeneracy and mass-sheet degeneracy |
Rinaldi & Del Pozzo (2024) | FIGARO: hierarchical non-parametric inference for population studies |
Rinaldi et al. (2024b) | Hierarchical inference of evidence using posterior samples |
Rinaldi (2024) | Accounting for selection biases in population analyses: equivalence of the in-likelihood and post-processing approaches |
Iorio et al. (2024) | The boring history of Gaia BH3 from isolated binary evolution |
Rinaldi et al. (2024a) | Evidence of evolution of the black hole mass function with redshift |
Dotti et al. (2023) | A fast test for the identification and confirmation of massive black hole binaries |
Morton et al. (2023) | GW190521: a binary black hole merger inside an active galactic nucleus? |
Sgalletta et al. (2023) | Binary neutron star populations in the Milky Way |
Rinaldi et al. (2023) | Systematic errors in the determination of the constant of gravitation |
Cheung et al. (2023) | Mitigating the effect of population model uncertainty on strong lensing Bayes factor using nonparametric methods |
Rinaldi & Del Pozzo (2022b) | Rapid localization of gravitational wave hosts with FIGARO |
Mastrogiovanni et al. (2022) | Cosmology with Gravitational Waves: a review |
Rinaldi & Del Pozzo (2022a) | (H)DPGMM: a hierarchy of Dirichlet process Gaussian mixture models for the inference of the black hole mass function |
Mastrogiovanni et al. (2021) | On the importance of source population models for gravitational-wave cosmology |
Resources
| Link | Description |
|---|---|
Demoblack group | The Demoblack group in Padova/Heidelberg |
RayNest | Parallel nested sampling in Python |
FIGARO | Multivariate probability density estimator |
Conjugate priors | Everything you need to know about the conjugate priors to the Gaussian distribution |