Deep Bayesian experimental design for quantum many-body systems
Bayesian experimental design is a technique that allows to efficiently select measurements to characterize a physical system by maximizing the expected information gain. Recent developments in deep neural networks and normalizing flows allow for a more efficient approximation of the posterior and th...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
IOP Publishing
2023-01-01
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| Series: | Machine Learning: Science and Technology |
| Subjects: | |
| Online Access: | https://doi.org/10.1088/2632-2153/ad020d |