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08/23/2023
An Intentional Forgetting-Driven Self-Healing Method For Deep Reinforcement Learning Systems
Deep reinforcement learning (DRL) is increasingly applied in large-scale...
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09/07/2022
SmOOD: Smoothness-based Out-of-Distribution Detection Approach for Surrogate Neural Networks in Aircraft Design
Aircraft industry is constantly striving for more efficient design optim...
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09/07/2022
Physics-Guided Adversarial Machine Learning for Aircraft Systems Simulation
In the context of aircraft system performance assessment, deep learning ...
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07/13/2022
DiverGet: A Search-Based Software Testing Approach for Deep Neural Network Quantization Assessment
Quantization is one of the most applied Deep Neural Network (DNN) compre...
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04/01/2022
Testing Feedforward Neural Networks Training Programs
Nowadays, we are witnessing an increasing effort to improve the performa...
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07/28/2021
Models of Computational Profiles to Study the Likelihood of DNN Metamorphic Test Cases
Neural network test cases are meant to exercise different reasoning path...
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05/17/2021
Automatic Fault Detection for Deep Learning Programs Using Graph Transformations
Nowadays, we are witnessing an increasing demand in both corporates and ...
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01/01/2021
Faults in Deep Reinforcement Learning Programs: A Taxonomy and A Detection Approach
A growing demand is witnessed in both industry and academia for employin...
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09/05/2019
DeepEvolution: A Search-Based Testing Approach for Deep Neural Networks
The increasing inclusion of Deep Learning (DL) models in safety-critical...
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09/05/2019
TFCheck : A TensorFlow Library for Detecting Training Issues in Neural Network Programs
The increasing inclusion of Machine Learning (ML) models in safety criti...
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12/05/2018
