21 citations · 48 across the 5 of their papers we have counts for
5 papers
Latent space projection predictive inference
Alejandro Catalina, Paul Bürkner, Aki Vehtari
Given a reference model that includes all the available variables, projection predictive inference replaces its posterior with a constrained projection including only a subset of a…
Challenges and Opportunities in High-dimensional Variational Inference
Akash Kumar Dhaka, Alejandro Catalina, Manushi Welandawe +3
Current black-box variational inference (BBVI) methods require the user to make numerous design choices -- such as the selection of variational objective and approximating family -…
Projection Predictive Inference for Generalized Linear and Additive Multilevel Models
Alejandro Catalina, Paul-Christian Bürkner, Aki Vehtari
Projection predictive inference is a decision theoretic Bayesian approach that decouples model estimation from decision making. Given a reference model previously built including a…
Robust, Accurate Stochastic Optimization for Variational Inference
Akash Kumar Dhaka, Alejandro Catalina, Michael Riis Andersen +3
We consider the problem of fitting variational posterior approximations using stochastic optimization methods. The performance of these approximations depends on (1) how well the v…
Group Heterogeneity Assessment for Multilevel Models
Topi Paananen, Alejandro Catalina, Paul-Christian Bürkner +1
Many data sets contain an inherent multilevel structure, for example, because of repeated measurements of the same observational units. Taking this structure into account is critic…