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In-Simulation Testing of Deep Learning Vision Models in Autonomous Robotic Manipulators
Testing autonomous robotic manipulators (ARMs) is challenging due to the complex software interactions between vision and control …
Dmytro Humeniuk, Houssem Ben Braiek, Thomas Reid, Foutse Khomh
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An Intentional Forgetting-Driven Self-Healing Method For Deep Reinforcement Learning Systems
Deep reinforcement learning (DRL) is increasingly applied in large-scale productions like Netflix and Facebook. As with most …
Ahmed Haj Yahmed, Rached Bouchoucha, Houssem Ben Braiek, Foutse Khomh
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SmOOD: Smoothness-based Out-of-Distribution Detection Approach for Surrogate Neural Networks in Aircraft Design
Aircraft industry is constantly striving for more efficient design optimization methods in terms of human efforts, computation time, …
Houssem Ben Braiek, Ali Tfaily, Foutse Khomh, Thomas Reid, Ciro Guida
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Models of Computational Profiles to Study the Likelihood of DNN Metamorphic Test Cases
Neural network test cases are meant to exercise different reasoning paths in an architecture and used to validate the prediction …
Ettore Merlo, Mira Marhaba, Foutse Khomh, Houssem Ben Braiek, Giuliano Antoniol
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The Scent of Deep Learning Code: An Empirical Study
Deep learning practitioners are often interested in improving their model accuracy rather than the interpretability of their models. As …
Hadhemi Jebnoun, Houssem Ben Braiek, Mohammad Masudur Rahman, Foutse Khomh
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DeepEvolution: A Search-Based Testing Approach for Deep Neural Networks
The increasing inclusion of Deep Learning (DL) models in safety-critical systems such as autonomous vehicles have led to the …
Houssem Ben Braiek, Foutse Khomh
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TFCheck : A TensorFlow Library for Detecting Training Issues in Neural Network Programs
The increasing inclusion of Machine Learning (ML) models in safety-critical systems like autonomous cars have led to the development of …
Houssem Ben Braiek, Foutse Khomh
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The Open-Closed Principle of Modern Machine Learning Frameworks'
Recent advances in computing technologies and the availability of huge volumes of data have sparked a new machine learning (ML) …
Houssem Ben Braiek, Foutse Khomh, Bram Adams
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