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04/05/2023
Adopting Two Supervisors for Efficient Use of Large-Scale Remote Deep Neural Networks
Recent decades have seen the rise of large-scale Deep Neural Networks (D...
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12/14/2022
Uncertainty Quantification for Deep Neural Networks: An Empirical Comparison and Usage Guidelines
Deep Neural Networks (DNN) are increasingly used as components of larger...
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08/24/2022
CheapET-3: Cost-Efficient Use of Remote DNN Models
On complex problems, state of the art prediction accuracy of Deep Neural...
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07/21/2022
A Forgotten Danger in DNN Supervision Testing: Generating and Detecting True Ambiguity
Deep Neural Networks (DNNs) are becoming a crucial component of modern s...
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05/02/2022
Simple Techniques Work Surprisingly Well for Neural Network Test Prioritization and Active Learning (Replicability Study)
Test Input Prioritizers (TIP) for Deep Neural Networks (DNN) are an impo...
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03/10/2021
A Review and Refinement of Surprise Adequacy
Surprise Adequacy (SA) is one of the emerging and most promising adequac...
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02/01/2021
Fail-Safe Execution of Deep Learning based Systems through Uncertainty Monitoring
Modern software systems rely on Deep Neural Networks (DNN) when processi...
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12/29/2020
Uncertainty-Wizard: Fast and User-Friendly Neural Network Uncertainty Quantification
Uncertainty and confidence have been shown to be useful metrics in a wid...
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10/10/2019