8 citations · 13 across the 7 of their papers we have counts for
8 papers
Efficient Amortized Bayesian Inference for Markov Random Fields via Gradient-Informed Grid Selection
Laura Bazahica, Alejandra Avalos-Pacheco, Matthew Moores +1
Bayesian inference for models with intractable likelihoods, such as Markov random fields, poses a fundamental computational challenge due to the tradeoff between inferential accura…
Profile Graphical Models
Alejandra Avalos-Pacheco, Monia Lupparelli, Francesco C. Stingo
We introduce a novel class of graphical models, termed profile graphical models, that represent, within a single graph, how an external factor influences the dependence structure o…
Bayesian integrative factor analysis methods, with application in nutrition and genomics data
Mavis Liang, Blake Hansen, Alejandra Avalos-Pacheco +1
High-dimensional data are crucial in biomedical research. Integrating such data from multiple studies is a critical process that relies on the choice of advanced statistical models…
Probabilistic Programming with Sufficient Statistics for faster Bayesian Computation
Clemens Pichler, Jack Jewson, Alejandra Avalos-Pacheco
Probabilistic programming methods have revolutionised Bayesian inference, making it easier than ever for practitioners to perform Markov-chain-Monte-Carlo sampling from non-conjuga…
Bayesian Inference of Multiple Ising Models for Heterogeneous Public Opinion Survey Networks
Alejandra Avalos-Pacheco, Andrea Lazzerini, Monia Lupparelli +1
In public opinion studies, the relationships between opinions on different topics are likely to shift based on the characteristics of the respondents. Thus, understanding the compl…
Fast Variational Inference for Bayesian Factor Analysis in Single and Multi-Study Settings
Blake Hansen, Alejandra Avalos-Pacheco, Massimiliano Russo +1
Factors models are routinely used to analyze high-dimensional data in both single-study and multi-study settings. Bayesian inference for such models relies on Markov Chain Monte Ca…
Multi-study factor regression model: an application in nutritional epidemiology
Roberta De Vito, Alejandra Avalos-Pacheco
Diet is a risk factor for many diseases. In nutritional epidemiology, studying reproducible dietary patterns is critical to reveal important associations with health. However, it i…
Heterogeneous large datasets integration using Bayesian factor regression
Alejandra Avalos-Pacheco, David Rossell, Richard S. Savage
Two key challenges in modern statistical applications are the large amount of information recorded per individual, and that such data are often not collected all at once but in bat…