2 citations · 3 across the 5 of their papers we have counts for
5 papers
In-Simulation Testing of Deep Learning Vision Models in Autonomous Robotic Manipulators
Dmytro Humeniuk, Houssem Ben Braiek, Thomas Reid +1
Testing autonomous robotic manipulators is challenging due to the complex software interactions between vision and control components. A crucial element of modern robotic manipulat…
An Intentional Forgetting-Driven Self-Healing Method For Deep Reinforcement Learning Systems
Ahmed Haj Yahmed, Rached Bouchoucha, Houssem Ben Braiek +1
Deep reinforcement learning (DRL) is increasingly applied in large-scale productions like Netflix and Facebook. As with most data-driven systems, DRL systems can exhibit undesirabl…
Automatic Fault Detection for Deep Learning Programs Using Graph Transformations
Amin Nikanjam, Houssem Ben Braiek, Mohammad Mehdi Morovati +1
Nowadays, we are witnessing an increasing demand in both corporates and academia for exploiting Deep Learning (DL) to solve complex real-world problems. A DL program encodes the ne…
Faults in Deep Reinforcement Learning Programs: A Taxonomy and A Detection Approach
Amin Nikanjam, Mohammad Mehdi Morovati, Foutse Khomh +1
A growing demand is witnessed in both industry and academia for employing Deep Learning (DL) in various domains to solve real-world problems. Deep Reinforcement Learning (DRL) is t…
TFCheck : A TensorFlow Library for Detecting Training Issues in Neural Network Programs
Houssem Ben Braiek, Foutse Khomh
The increasing inclusion of Machine Learning (ML) models in safety critical systems like autonomous cars have led to the development of multiple model-based ML testing techniques.…