Certification of iterative predictions in Bayesian neural networks
We consider the problem of computing reach-avoid probabilities for iterative predictions made with Bayesian neural network (BNN) models. Specifically, we leverage bound propagation techniques and backward recursion to compute lower bounds for the probability that trajectories of the BNN model reach...
Main Authors: | Wicker, M, Laurenti, L, Patane, A, Paoletti, N, Abate, A, Kwiatkowska, M |
---|---|
Format: | Conference item |
Language: | English |
Published: |
Journal of Machine Learning Research
2021
|
Similar Items
-
Adversarial robustness certification for Bayesian neural networks
by: Wicker, M, et al.
Published: (2024) -
Probabilistic reach-avoid for Bayesian neural networks
by: Wicker, M, et al.
Published: (2024) -
Statistical guarantees for the robustness of Bayesian neural networks
by: Cardelli, L, et al.
Published: (2019) -
Probabilistic safety for bayesian neural networks
by: Wicker, M, et al.
Published: (2020) -
Safety guarantees for iterative predictions with Gaussian Processes
by: Polymenakos, K, et al.
Published: (2021)