17 citations · 22 across the 7 of their papers we have counts for
7 papers
A relax-fix-and-exclude algorithm for an MINLP problem with multilinear interpolations
Bruno Machado Pacheco, Pedro Marcolin Antunes, Eduardo Camponogara +4
This paper introduces a novel algorithm for Mixed-Integer Nonlinear Programming (MINLP) problems with multilinear interpolations of look-up tables. These problems arise when object…
Solving Differential Equations using Physics-Informed Deep Equilibrium Models
Bruno Machado Pacheco, Eduardo Camponogara
This paper introduces Physics-Informed Deep Equilibrium Models (PIDEQs) for solving initial value problems (IVPs) of ordinary differential equations (ODEs). Leveraging recent advan…
Soft Dice Confidence: A Near-Optimal Confidence Estimator for Selective Prediction in Semantic Segmentation
Bruno Laboissiere Camargos Borges, Bruno Machado Pacheco, Danilo Silva
In semantic segmentation, even state-of-the-art deep learning models fall short of the performance required in certain high-stakes applications such as medical image analysis. In t…
Deep-learning-based Early Fixing for Gas-lifted Oil Production Optimization: Supervised and Weakly-supervised Approaches
Bruno Machado Pacheco, Laio Oriel Seman, Eduardo Camponogara
Maximizing oil production from gas-lifted oil wells entails solving Mixed-Integer Linear Programs (MILPs). As the parameters of the wells, such as the basic-sediment-to-water ratio…
Does pre-training on brain-related tasks results in better deep-learning-based brain age biomarkers?
Bruno Machado Pacheco, Victor Hugo Rocha de Oliveira, Augusto Braga Fernandes Antunes +2
Brain age prediction using neuroimaging data has shown great potential as an indicator of overall brain health and successful aging, as well as a disease biomarker. Deep learning m…
Graph Neural Networks for the Offline Nanosatellite Task Scheduling Problem
Bruno Machado Pacheco, Laio Oriel Seman, Cezar Antonio Rigo +3
This study investigates how to schedule nanosatellite tasks more efficiently using Graph Neural Networks (GNNs). In the Offline Nanosatellite Task Scheduling (ONTS) problem, the go…
Towards fully automated deep-learning-based brain tumor segmentation: is brain extraction still necessary?
Bruno Machado Pacheco, Guilherme de Souza e Cassia, Danilo Silva
State-of-the-art brain tumor segmentation is based on deep learning models applied to multi-modal MRIs. Currently, these models are trained on images after a preprocessing stage th…