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339 Publications

2021 | Conference Paper | IST-REx-ID: 10667 | OA
M. Lechner, Ð. Žikelić, K. Chatterjee, and T. A. Henzinger, “Infinite time horizon safety of Bayesian neural networks,” in 35th Conference on Neural Information Processing Systems, Virtual, 2021.
View | Files available | DOI | Download Published Version (ext.) | arXiv
 
2021 | Conference Paper | IST-REx-ID: 10666 | OA
M. Lechner, R. Hasani, R. Grosu, D. Rus, and T. A. Henzinger, “Adversarial training is not ready for robot learning,” in 2021 IEEE International Conference on Robotics and Automation, Xi’an, China, 2021, pp. 4140–4147.
View | Files available | DOI | Download None (ext.) | arXiv
 
2021 | Conference Paper | IST-REx-ID: 10665 | OA
T. A. Henzinger, M. Lechner, and D. Zikelic, “Scalable verification of quantized neural networks,” in Proceedings of the AAAI Conference on Artificial Intelligence, Virtual, 2021, vol. 35, no. 5A, pp. 3787–3795.
View | Files available | Download Published Version (ext.) | arXiv
 
2021 | Conference Paper | IST-REx-ID: 10669 | OA
S. Grunbacher, R. Hasani, M. Lechner, J. Cyranka, S. A. Smolka, and R. Grosu, “On the verification of neural ODEs with stochastic guarantees,” in Proceedings of the AAAI Conference on Artificial Intelligence, Virtual, 2021, vol. 35, no. 13, pp. 11525–11535.
View | Files available | Download Published Version (ext.) | arXiv
 
2021 | Conference Paper | IST-REx-ID: 10671 | OA
R. Hasani, M. Lechner, A. Amini, D. Rus, and R. Grosu, “Liquid time-constant networks,” in Proceedings of the AAAI Conference on Artificial Intelligence, Virtual, 2021, vol. 35, no. 9, pp. 7657–7666.
View | Files available | Download Published Version (ext.) | arXiv
 

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