732 citations · 1.1k across the 16 of their papers we have counts for
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cs.LG2022★ 3 cited
Identifying the Context Shift between Test Benchmarks and Production Data
Matthew Groh
Machine learning models are often brittle on production data despite achieving high accuracy on benchmark datasets. Benchmark datasets have traditionally served dual purposes: firs…
cs.LG2018★ 3 cited
Evaluating Generative Adversarial Networks on Explicitly Parameterized Distributions
Shayne O'Brien, Matt Groh, Abhimanyu Dubey
The true distribution parameterizations of commonly used image datasets are inaccessible. Rather than designing metrics for feature spaces with unknown characteristics, we propose…