Infinite time horizon safety of Bayesian neural networks
Bayesian neural networks (BNNs) place distributions over the weights of a neural network to model uncertainty in the data and the network’s prediction. We consider the problem of verifying safety when running a Bayesian neural network policy in a feedback loop with infinite time horizon systems. Com...
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| Main Authors: | , , , |
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| Format: | text |
| Language: | English |
| Published: |
Institutional Knowledge at Singapore Management University
2021
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| Subjects: | |
| Online Access: | https://ink.library.smu.edu.sg/sis_research/9066 https://ink.library.smu.edu.sg/context/sis_research/article/10069/viewcontent/NeurIPS_2021_infinite_time_horizon_safety_of_bayesian_neural_networks_Paper.pdf |
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| Institution: | Singapore Management University |
| Language: | English |
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