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Found 2 papers, 1 papers with code
Active Learning with Expected Error Reduction
In this paper we reformulate EER under the lens of Bayesian active learning and derive a computationally efficient version that can use any Bayesian parameter sampling method (such as arXiv:1506. 02142).
Evaluating Generative Adversarial Networks on Explicitly Parameterized Distributions
The true distribution parameterizations of commonly used image datasets are inaccessible.
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