Syntactic vs Semantic Linear Abstraction and Refinement of Neural Networks-Reference-Cited by-同舟云学术

Syntactic vs Semantic Linear Abstraction and Refinement of Neural Networks

Published:2023 Issue: Volume: Page:401-421
ISSN:0302-9743
Container-title:Automated Technology for Verification and Analysis
language:
Short-container-title:

Author:

Chau Calvin^ORCID,Křetínský Jan^ORCID,Mohr Stefanie^ORCID

Publisher

Springer Nature Switzerland

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-45329-8_19

Reference34 articles.

1. Altschuler, J., et al.: Greedy column subset selection: new bounds and distributed algorithms. In: Balcan, M., Weinberger, K.Q. (eds.) Proceedings of the 33nd International Conference on Machine Learning, ICML, New York City, NY, USA, vol. 48, pp. 2539–2548. JMLR Workshop and Conference Proceedings. JMLR.org (2016)

2. Lecture Notes in Computer Science;P Ashok,2020

3. Information Science and Statistics;CM Bishop,2007

4. Brix, C., et al.: First three years of the international verification of neural networks competition (VNN-COMP). Int. J. Softw. Tools Technol. Transfer 1–11 (2023). https://doi.org/10.1007/s10009-023-00703-4

5. Caruana, R., Lawrence, S., Giles, C.: Overfitting in neural nets: backpropagation, conjugate gradient, and early stopping. In: Leen, T., Dietterich, T., Tresp, V. (eds.) Advances in Neural Information Processing Systems, vol. 13. MIT Press (2000)

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Unifying Syntactic and Semantic Abstractions for Deep Neural Networks;Lecture Notes in Computer Science;2024

2. On applying residual reasoning within neural network verification;Software and Systems Modeling;2023-11-16

3. Syntactic vs Semantic Linear Abstraction and Refinement of Neural Networks;Automated Technology for Verification and Analysis;2023