Michael Weiss | DeepAI

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Featured Co-authors

Paolo Tonella
22 publications
Andrea Stocco
6 publications
Rwiddhi Chakraborty
3 publications
André García Gómez
1 publication
Marco Calzana
1 publication

∙ 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...

0 Michael Weiss, et al. ∙

∙ 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...

0 Michael Weiss, et al. ∙

∙ 08/24/2022

CheapET-3: Cost-Efficient Use of Remote DNN Models

On complex problems, state of the art prediction accuracy of Deep Neural...

0 Michael Weiss, et al. ∙

∙ 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...

11 Michael Weiss, et al. ∙

∙ 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...

0 Michael Weiss, et al. ∙

∙ 03/10/2021

A Review and Refinement of Surprise Adequacy

Surprise Adequacy (SA) is one of the emerging and most promising adequac...

0 Michael Weiss, et al. ∙

∙ 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...

0 Michael Weiss, et al. ∙

∙ 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...

0 Michael Weiss, et al. ∙

∙ 10/10/2019

Misbehaviour Prediction for Autonomous Driving Systems

Deep Neural Networks (DNNs) are the core component of modern autonomous ...

0 Andrea Stocco, et al. ∙