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We propose a robust and reliable evaluation metric for generative models by introducing topological and statistical treatments for rigorous support estimation.
Error detecting and error correcting codes
Richard W Hamming · 1950
Earlier work this paper cites.
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Herbert Federer · 1959
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Extensions of Lipschitz mappings into a Hilbert space
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Earlier work this paper cites.
Strong approximation of density estimators from weakly dependent observations by density estimators from independent observations
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Earlier work this paper cites.
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Tim Salimans, Ian Goodfellow, Wojciech Zaremba, Vicki Cheung, Alec Radford, and Xi Chen · 2016
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Muhammad Ferjad Naeem, Seong Joon Oh, Youngjung Uh, Yunjey Choi, and Jaejun Yoo · 2020
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Identifying mislabeled data using the area under the margin ranking
Geoff Pleiss, Tianyi Zhang, Ethan Elenberg, and Kilian Q Weinberger · 2020
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On self-supervised image representations for gan evaluation
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