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mweiss.ch

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Scopus Author ID: 57198623419
Scopus Author ID: 57002022700

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Switzerland

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Employment (1)

Università della Svizzera Italiana: Lugano, TI, CH

2019-05-19 to present | PhD Student (Software Institute)
Employment
Source: Self-asserted source
Michael Weiss

Works (13)

Adopting Two Supervisors for Efficient Use of Large-Scale Remote Deep Neural Networks

ACM Transactions on Software Engineering and Methodology
2024-01-31 | Journal article
DOI: 10.1145/3617593
Contributors: Michael Weiss; Paolo Tonella
Source: check_circle
Crossref

Adopting Two Supervisors for Efficient Use of Large-Scale Remote Deep Neural Networks - RCR Report

ACM Transactions on Software Engineering and Methodology
2024-01-31 | Journal article
DOI: 10.1145/3617594
Contributors: Michael Weiss; Paolo Tonella
Source: check_circle
Crossref

Generating and detecting true ambiguity: a forgotten danger in DNN supervision testing

Empirical Software Engineering
2023-11 | Journal article
DOI: 10.1007/s10664-023-10393-w
Contributors: Michael Weiss; André García Gómez; Paolo Tonella
Source: check_circle
Crossref

Uncertainty quantification for deep neural networks: An empirical comparison and usage guidelines

Software Testing, Verification and Reliability
2023-09 | Journal article
DOI: 10.1002/stvr.1840
Contributors: Michael Weiss; Paolo Tonella
Source: check_circle
Crossref

CheapET-3: cost-efficient use of remote DNN models

Proceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering
2022-11-09 | Other
DOI: 10.1145/3540250.3559082
Contributors: Michael Weiss
Source: Self-asserted source
Michael Weiss via Crossref Metadata Search

Simple techniques work surprisingly well for neural network test prioritization and active learning (replicability study)

Proceedings of the 31st ACM SIGSOFT International Symposium on Software Testing and Analysis
2022-07 | Other
DOI: 10.1145/3533767.3534375
Contributors: Michael Weiss; Paolo Tonella
Source: Self-asserted source
Michael Weiss via Crossref Metadata Search

A Review and Refinement of Surprise Adequacy

2021 IEEE/ACM Third International Workshop on Deep Learning for Testing and Testing for Deep Learning (DeepTest)
2021-06 | Other
DOI: 10.1109/deeptest52559.2021.00009
Contributors: Michael Weiss; Rwiddhi Chakraborty; Paolo Tonella
Source: Self-asserted source
Michael Weiss via Crossref Metadata Search

Fail-Safe Execution of Deep Learning based Systems through Uncertainty Monitoring

2021 14th IEEE Conference on Software Testing, Verification and Validation (ICST)
2021-04 | Other
DOI: 10.1109/icst49551.2021.00015
Contributors: Michael Weiss; Paolo Tonella
Source: Self-asserted source
Michael Weiss via Crossref Metadata Search

Uncertainty-Wizard: Fast and User-Friendly Neural Network Uncertainty Quantification

2021 14th IEEE Conference on Software Testing, Verification and Validation (ICST)
2021-04 | Other
DOI: 10.1109/icst49551.2021.00056
Contributors: Michael Weiss; Paolo Tonella
Source: Self-asserted source
Michael Weiss via Crossref Metadata Search

Misbehaviour prediction for autonomous driving systems

Proceedings - International Conference on Software Engineering
2020 | Conference paper
DOI: 10.1145/3377811.3380353
EID:

2-s2.0-85094321490

Part of ISBN:

02705257
Contributors: Stocco, A.; Weiss, M.; Calzana, M.; Tonella, P.
Source: Self-asserted source
Michael Weiss via Scopus - Elsevier

Testing machine learning based systems: a systematic mapping

Empirical Software Engineering
2020 | Journal article
DOI: 10.1007/s10664-020-09881-0
EID:

2-s2.0-85091048368

Part of ISBN:

15737616 13823256
Contributors: Riccio, V.; Jahangirova, G.; Stocco, A.; Humbatova, N.; Weiss, M.; Tonella, P.
Source: Self-asserted source
Michael Weiss via Scopus - Elsevier

SATS: A universal spectrum auction test suite

Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS
2017 | Conference paper
EID:

2-s2.0-85031940150

Part of ISBN:

15582914 15488403
Contributors: Weiss, M.; Lubin, B.; Seuken, S.
Source: Self-asserted source
Michael Weiss via Scopus - Elsevier

The power of local manipulation strategies in assignment mechanisms

IJCAI International Joint Conference on Artificial Intelligence
2015 | Conference paper
EID:

2-s2.0-84949748016

Part of ISBN:

10450823
Contributors: Mennle, T.; Weiss, M.; Philipp, B.; Seuken, S.
Source: Self-asserted source
Michael Weiss via Scopus - Elsevier
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