A kernelised Stein statistic for assessing implicit generative models
Synthetic data generation has become a key ingredient for training machine learning procedures, addressing tasks such as data augmentation, analysing privacy-sensitive data, or visualising representative samples. Assessing the quality of such synthetic data generators hence has to be addressed. As (...
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| Format: | Conference item |
| Language: | English |
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Curran Associates
2023
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