activity
20182021
most citedA machine learning approach for underwater gas leakage detection

6 citations · 6 across the 2 of their papers we have counts for

collaborators

5 papers

stat.AP2021

Estimating the radii of air bubbles in water using passive acoustic monitoring

Paulo Hubert, Linilson Padovese

The study of the acoustic emission of underwater gas bubbles is a subject of both theoretical and applied interest, since it finds an important application in the development of ac…

stat.ML2020

Probabilistic learning of boolean functions applied to the binary classification problem with categorical covariates

Paulo Hubert

In this work we cast the problem of binary classification in terms of estimating a partition on Bernoulli data. When the explanatory variables are all categorical, the problem can…

stat.ML20196 cited

A machine learning approach for underwater gas leakage detection

Paulo Hubert, Linilson Padovese

Underwater gas reservoirs are used in many situations. In particular, Carbon Capture and Storage (CCS) facilities that are currently being developed intend to store greenhouse gase…

stat.AP2019

A Bayesian binary algorithm for RMS-based acoustic signal segmentation

Paulo Hubert, Rebecca Killick, Alexandra Chung +1

Changepoint analysis (also known as segmentation analysis) aims at analyzing an ordered, one-dimensional vector, in order to find locations where some characteristic of the data ch…

stat.CO2018

Fast Implementation of a Bayesian Unsupervised Segmentation Algorithm

Paulo Hubert, Linilson Padovese, Julio Stern

In a recent paper, we have proposed an unsupervised algorithm for audio signal segmentation entirely based on Bayesian methods. In its first implementation, however, the method sho…