Marabou 2.0: A Versatile Formal Analyzer of Neural Networks

Haoze Wu; Omri Isac; Aleksandar Zeljić; Teruhiro Tagomori; Matthew Daggitt; Wen Kokke; Idan Refaeli; Guy Amir; Kyle Julian; Shahaf Bassan; Pei Huang; Ori Lahav; Min Wu; Min Zhang; Ekaterina Komendantskaya; Guy Katz; Clark Barrett

doi:https://doi.org/10.1007/978-3-031-65630-9_13

Marabou 2.0: A Versatile Formal Analyzer of Neural Networks

Haoze Wu, Omri Isac, Aleksandar Zeljić, Teruhiro Tagomori, Matthew Daggitt, Wen Kokke, Idan Refaeli, Guy Amir, Kyle Julian, Shahaf Bassan, Pei Huang, Ori Lahav, Min Wu, Min Zhang, Ekaterina Komendantskaya, Guy Katz, Clark Barrett

The Rachel and Selim Benin School of Engineering and Computer Science

The Hebrew University of Jerusalem

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

This paper serves as a comprehensive system description of version 2.0 of the Marabou framework for formal analysis of neural networks. We discuss the tool’s architectural design and highlight the major features and components introduced since its initial release.

Original language	English
Title of host publication	Computer Aided Verification - 36th International Conference, CAV 2024, Proceedings
Editors	Arie Gurfinkel, Vijay Ganesh
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	249-264
Number of pages	16
ISBN (Print)	9783031656293
DOIs	https://doi.org/10.1007/978-3-031-65630-9_13
State	Published - 2024
Event	36th International Conference on Computer Aided Verification, CAV 2024 - Montreal, Canada Duration: 24 Jul 2024 → 27 Jul 2024

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	14682 LNCS

Conference

Conference	36th International Conference on Computer Aided Verification, CAV 2024
Country/Territory	Canada
City	Montreal
Period	24/07/24 → 27/07/24

All Science Journal Classification (ASJC) codes

Theoretical Computer Science
General Computer Science

Access to Document

https://doi.org/10.1007/978-3-031-65630-9_13

Cite this

Wu, H., Isac, O., Zeljić, A., Tagomori, T., Daggitt, M., Kokke, W., Refaeli, I., Amir, G., Julian, K., Bassan, S., Huang, P., Lahav, O., Wu, M., Zhang, M., Komendantskaya, E., Katz, G., & Barrett, C. (2024). Marabou 2.0: A Versatile Formal Analyzer of Neural Networks. In A. Gurfinkel, & V. Ganesh (Eds.), Computer Aided Verification - 36th International Conference, CAV 2024, Proceedings (pp. 249-264). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 14682 LNCS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-65630-9_13

Wu, Haoze ; Isac, Omri ; Zeljić, Aleksandar et al. / Marabou 2.0 : A Versatile Formal Analyzer of Neural Networks. Computer Aided Verification - 36th International Conference, CAV 2024, Proceedings. editor / Arie Gurfinkel ; Vijay Ganesh. Springer Science and Business Media Deutschland GmbH, 2024. pp. 249-264 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "This paper serves as a comprehensive system description of version 2.0 of the Marabou framework for formal analysis of neural networks. We discuss the tool{\textquoteright}s architectural design and highlight the major features and components introduced since its initial release.",

author = "Haoze Wu and Omri Isac and Aleksandar Zelji{\'c} and Teruhiro Tagomori and Matthew Daggitt and Wen Kokke and Idan Refaeli and Guy Amir and Kyle Julian and Shahaf Bassan and Pei Huang and Ori Lahav and Min Wu and Min Zhang and Ekaterina Komendantskaya and Guy Katz and Clark Barrett",

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year = "2024",

doi = "https://doi.org/10.1007/978-3-031-65630-9_13",

language = "الإنجليزيّة",

isbn = "9783031656293",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Science and Business Media Deutschland GmbH",

pages = "249--264",

editor = "Arie Gurfinkel and Vijay Ganesh",

booktitle = "Computer Aided Verification - 36th International Conference, CAV 2024, Proceedings",

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Wu, H, Isac, O, Zeljić, A, Tagomori, T, Daggitt, M, Kokke, W, Refaeli, I, Amir, G, Julian, K, Bassan, S, Huang, P, Lahav, O, Wu, M, Zhang, M, Komendantskaya, E, Katz, G & Barrett, C 2024, Marabou 2.0: A Versatile Formal Analyzer of Neural Networks. in A Gurfinkel & V Ganesh (eds), Computer Aided Verification - 36th International Conference, CAV 2024, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 14682 LNCS, Springer Science and Business Media Deutschland GmbH, pp. 249-264, 36th International Conference on Computer Aided Verification, CAV 2024, Montreal, Canada, 24/07/24. https://doi.org/10.1007/978-3-031-65630-9_13

Marabou 2.0: A Versatile Formal Analyzer of Neural Networks. / Wu, Haoze; Isac, Omri; Zeljić, Aleksandar et al.
Computer Aided Verification - 36th International Conference, CAV 2024, Proceedings. ed. / Arie Gurfinkel; Vijay Ganesh. Springer Science and Business Media Deutschland GmbH, 2024. p. 249-264 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 14682 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Marabou 2.0

T2 - 36th International Conference on Computer Aided Verification, CAV 2024

AU - Wu, Haoze

AU - Isac, Omri

AU - Zeljić, Aleksandar

AU - Tagomori, Teruhiro

AU - Daggitt, Matthew

AU - Kokke, Wen

AU - Refaeli, Idan

AU - Amir, Guy

AU - Julian, Kyle

AU - Bassan, Shahaf

AU - Huang, Pei

AU - Lahav, Ori

AU - Wu, Min

AU - Zhang, Min

AU - Komendantskaya, Ekaterina

AU - Katz, Guy

AU - Barrett, Clark

PY - 2024

Y1 - 2024

N2 - This paper serves as a comprehensive system description of version 2.0 of the Marabou framework for formal analysis of neural networks. We discuss the tool’s architectural design and highlight the major features and components introduced since its initial release.

AB - This paper serves as a comprehensive system description of version 2.0 of the Marabou framework for formal analysis of neural networks. We discuss the tool’s architectural design and highlight the major features and components introduced since its initial release.

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U2 - https://doi.org/10.1007/978-3-031-65630-9_13

DO - https://doi.org/10.1007/978-3-031-65630-9_13

M3 - منشور من مؤتمر

SN - 9783031656293

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 249

EP - 264

BT - Computer Aided Verification - 36th International Conference, CAV 2024, Proceedings

A2 - Gurfinkel, Arie

A2 - Ganesh, Vijay

PB - Springer Science and Business Media Deutschland GmbH

Y2 - 24 July 2024 through 27 July 2024

ER -

Wu H, Isac O, Zeljić A, Tagomori T, Daggitt M, Kokke W et al. Marabou 2.0: A Versatile Formal Analyzer of Neural Networks. In Gurfinkel A, Ganesh V, editors, Computer Aided Verification - 36th International Conference, CAV 2024, Proceedings. Springer Science and Business Media Deutschland GmbH. 2024. p. 249-264. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: https://doi.org/10.1007/978-3-031-65630-9_13

Marabou 2.0: A Versatile Formal Analyzer of Neural Networks

Abstract

Publication series

Conference

All Science Journal Classification (ASJC) codes

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