An unfolding method based on conditional invertible neural networks (cINN) using iterative training
The unfolding of detector effects is crucial for the comparison of data to theory predictions. While traditional methods are limited to representing the data in a low number of dimensions, machine learning has enabled new unfolding techniques while retaining the full dimensionality. Generative netwo...
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| Format: | Article |
| Language: | English |
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SciPost
2024-02-01
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| Series: | SciPost Physics Core |
| Online Access: | https://scipost.org/SciPostPhysCore.7.1.007 |