4 papers
Bayesian Variable Selection in Generalized Linear Models
Lucia Filippozzi, Iñigo Urteaga, Claudio Agostinelli
Covariate selection in Generalized Linear Models (GLMs) is a fundamental problem in statistics, as including irrelevant predictors might lead to overfitting and poor interpretabili…
Anomaly detection in time-series via inductive biases in the latent space of conditional normalizing flows
David Baumgartner, Eliezer de Souza da Silva, Iñigo Urteaga
Deep generative models for anomaly detection in multivariate time-series are typically trained by maximizing observed data likelihood. However, likelihood in observation space meas…
Probabilistic Shapley Value Modeling and Inference
Mert Ketenci, Iñigo Urteaga, Victor Alfonso Rodriguez +2
We propose probabilistic Shapley inference (PSI), a novel probabilistic framework to model and infer sufficient statistics of feature attributions in flexible predictive models, vi…
Accurate and Scalable Stochastic Gaussian Process Regression via Learnable Coreset-based Variational Inference
Mert Ketenci, Adler Perotte, Noémie Elhadad +1
We introduce a novel stochastic variational inference method for Gaussian process () regression, by deriving a posterior over a learnable set of coresets: i.e., over…