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Joris Guérin

2 accepted papers

2024

Can we Defend Against the Unknown? An Empirical Study About Threshold Selection for Neural Network Monitoring

UAI 2024poster

With the increasing use of neural networks in critical systems, runtime monitoring becomes essential to reject unsafe predictions during inference. Various techniques have emerged to establish rejection scores that maximize the separability between the distributions of safe and unsafe predictions. T…

Cited by 1SourcePDFScholar
2018

Semantically Meaningful View Selection

IROS 2018poster

An understanding of the nature of objects could help robots to solve both high-level abstract tasks and improve performance at lower-level concrete tasks. Although deep learning has facilitated progress in image understanding, a robot's performance in problems like object recognition often depends o…

Cited by 12SourcecodeScholar