162 citations · 216 across the 18 of their papers we have counts for
20 papers
Markov Stick-breaking Processes
María F. Gil-Leyva, Antonio Lijoi, Ramsés H. Mena +1
Stick-breaking has a long history and is one of the most popular procedures for constructing random discrete distributions in Statistics and Machine Learning. In particular, due to…
Exact two-stage finite-mixture representations for species sampling processes
Ramsés H. Mena, Christos Merkatas, Theodoros Nicoleris +1
Discrete random probability measures are central to Bayesian inference, particularly as priors for mixture modeling and clustering. A broad and unifying class is that of proper spe…
Weighted Support Points from Random Measures: An Interpretable Alternative for Generative Modeling
Peiqi Zhao, Carlos E. Rodríguez, Ramsés H. Mena +1
Support points summarize a large dataset through a smaller set of representative points that can be used for data operations, such as Monte Carlo integration, without requiring acc…
Reconstruction of the Probability Measure and the Coupling Parameters in a Curie-Weiss Model
Miguel Ballesteros, Ramsés H. Mena, Arno Siri-Jégousse +1
The Curie-Weiss model is used to study phase transitions in statistical mechanics and has been the object of rigorous analysis in mathematical physics. We analyse the problem of re…
Detection of an Arbitrary Number of Communities in a Block Spin Ising Model
Miguel Ballesteros, Ramsés H. Mena, José Luis Pérez +1
We study the problem of community detection in a general version of the block spin Ising model featuring M groups, a model inspired by the Curie-Weiss model of ferromagnetism in st…
On a divergence-based prior analysis of stick-breaking processes
José A. Perusquía, Mario Diaz, Ramsés H. Mena
The nonparametric view of Bayesian inference has transformed statistics and many of its applications. The canonical Dirichlet process and other more general families of nonparametr…