Robustness of 3D deep learning in an adversarial setting
Understanding the spatial arrangement and nature of real-world objects is of paramount importance to many complex engineering tasks, including autonomous navigation. Deep learning has revolutionized state-of-the-art performance for tasks in 3D environments; however, relatively little is known about...
Autori principali: | Wicker, M, Kwiatkowska, M |
---|---|
Natura: | Conference item |
Lingua: | English |
Pubblicazione: |
IEEE
2020
|
Documenti analoghi
-
Adversarial robustness certification for Bayesian neural networks
di: Wicker, M, et al.
Pubblicazione: (2024) -
Bayesian inference with certifiable adversarial robustness
di: Wicker, M, et al.
Pubblicazione: (2021) -
Adversarial robustness of Bayesian neural networks
di: Wicker, M
Pubblicazione: (2021) -
Adversarial robustness of deep reinforcement learning
di: Qu, Xinghua
Pubblicazione: (2022) -
Adversarial robustness guarantees for Gaussian processes
di: Patane, A, et al.
Pubblicazione: (2022)