activity
20192024
most citedEfficiently resolving rotational ambiguity in Bayesian matrix sampling with matching

5 citations · 6 across the 3 of their papers we have counts for

collaborators

5 papers

stat.ML2024

Bayesian Joint Additive Factor Models for Multiview Learning

Niccolo Anceschi, Federico Ferrari, David B. Dunson +1

It is increasingly common to collect data of multiple different types on the same set of samples. Our focus is on studying relationships between such multiview features and respons…

stat.CO2021★ 5 cited

Efficiently resolving rotational ambiguity in Bayesian matrix sampling with matching

Evan Poworoznek, Niccolo Anceschi, Federico Ferrari +1

A wide class of Bayesian models involve unidentifiable random matrices that display rotational ambiguity, with the Gaussian factor model being a typical example. A rich variety of…

stat.AP2019★ 1 cited

Identifying main effects and interactions among exposures using Gaussian processes

Federico Ferrari, David B. Dunson

This article is motivated by the problem of studying the joint effect of different chemical exposures on human health outcomes. This is essentially a nonparametric regression probl…

stat.AP2019

Nonparametric Bayesian multi-armed bandits for single cell experiment design

Federico Camerlenghi, Bianca Dumitrascu, Federico Ferrari +2

The problem of maximizing cell type discovery under budget constraints is a fundamental challenge for the collection and analysis of single-cell RNA-sequencing (scRNA-seq) data. In…

stat.ME2019

Bayesian Factor Analysis for Inference on Interactions

Federico Ferrari, David B Dunson

This article is motivated by the problem of inference on interactions among chemical exposures impacting human health outcomes. Chemicals often co-occur in the environment or in sy…