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ORCIDNSV/FoMLAS@CAV 2022: Haifa, Israel
- Omri Isac, Radoslav Ivanov
, Guy Katz, Nina Narodytska, Laura Nenzi:
Software Verification and Formal Methods for ML-Enabled Autonomous Systems - 5th International Workshop, FoMLAS 2022, and 15th International Workshop, NSV 2022, Haifa, Israel, July 31 - August 1, and August 11, 2022, Proceedings. Lecture Notes in Computer Science 13466, Springer 2022, ISBN 978-3-031-21221-5
FoMLAS 2022
- Youcheng Sun, Muhammad Usman, Divya Gopinath, Corina S. Pasareanu:
VPN: Verification of Poisoning in Neural Networks. 3-14 - Ravi Mangal, Corina S. Pasareanu:
A Cascade of Checkers for Run-time Certification of Local Robustness. 15-28 - João Batista Pereira Matos Jr., Iury Bessa, Edoardo Manino, Xidan Song, Lucas C. Cordeiro:
CEG4N: Counter-Example Guided Neural Network Quantization Refinement. 29-45 - Idan Refaeli, Guy Katz:
Minimal Multi-Layer Modifications of Deep Neural Networks. 46-66 - Natalia Slusarz, Ekaterina Komendantskaya, Matthew L. Daggitt, Robert J. Stewart:
Differentiable Logics for Neural Network Training and Verification. 67-77 - Remi Desmartin, Grant O. Passmore, Ekaterina Komendantskaya:
Neural Networks in Imandra: Matrix Representation as a Verification Choice. 78-95 - Klas Leino, Aymeric Fromherz, Ravi Mangal, Matt Fredrikson, Bryan Parno, Corina S. Pasareanu:
Self-correcting Neural Networks for Safe Classification. 96-130 - Saddek Bensalem, Chih-Hong Cheng, Xiaowei Huang, Panagiotis Katsaros, Adam Molin, Dejan Nickovic, Doron Peled:
Formal Specification for Learning-Enabled Autonomous Systems. 131-143
NSV 2022
- Ariel E. Kellison, Andrew W. Appel:
Verified Numerical Methods for Ordinary Differential Equations. 147-163 - Quentin Ferro, Stef Graillat, Thibault Hilaire, Fabienne Jézéquel, Basile Lewandowski:
Neural Network Precision Tuning Using Stochastic Arithmetic. 164-186 - Gokul Hariharan, Brian Kempa, Tichakorn Wongpiromsarn, Phillip H. Jones, Kristin Y. Rozier:
MLTL Multi-type (MLTLM): A Logic for Reasoning About Signals of Different Types. 187-204
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