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Autor:
Banerjee, Pronoma, Gude, Manasi V, Sampat, Rajvi J, Hedaoo, Sharvari M, Dhavala, Soma, Saha, Snehanshu
Machine learning models are often misspecified in the likelihood, which leads to a lack of robustness in the predictions. In this paper, we introduce a framework for correcting likelihood misspecifications in several paradigm agnostic noisy prior mod
Externí odkaz:
http://arxiv.org/abs/2304.03805
