14 citations · 23 across the 3 of their papers we have counts for
3 papers
cs.CR2021★ 1 cited
Datasets are not Enough: Challenges in Labeling Network Traffic
Jorge Guerra, Carlos Catania, Eduardo Veas
In contrast to previous surveys, the present work is not focused on reviewing the datasets used in the network security field. The fact is that many of the available public labeled…
cs.LG2021★ 8 cited
XAI Methods for Neural Time Series Classification: A Brief Review
Ilija Šimić, Vedran Sabol, Eduardo Veas
Deep learning models have recently demonstrated remarkable results in a variety of tasks, which is why they are being increasingly applied in high-stake domains, such as industry,…
cs.AI2021★ 14 cited
Formula RL: Deep Reinforcement Learning for Autonomous Racing using Telemetry Data
Adrian Remonda, Sarah Krebs, Eduardo Veas +2
This paper explores the use of reinforcement learning (RL) models for autonomous racing. In contrast to passenger cars, where safety is the top priority, a racing car aims to minim…