2 citations · 4 across the 4 of their papers we have counts for
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cs.LG2020
ATOM: Robustifying Out-of-distribution Detection Using Outlier Mining
Jiefeng Chen, Yixuan Li, Xi Wu +2
Detecting out-of-distribution (OOD) inputs is critical for safely deploying deep learning models in an open-world setting. However, existing OOD detection solutions can be brittle…
cs.LG2020
Representation Bayesian Risk Decompositions and Multi-Source Domain Adaptation
Xi Wu, Yang Guo, Jiefeng Chen +3
We consider representation learning (hypothesis class ) where training and test distributions can be different. Recent studies provide hi…
cs.LG2020
Robust Out-of-distribution Detection for Neural Networks
Jiefeng Chen, Yixuan Li, Xi Wu +2
Detecting out-of-distribution (OOD) inputs is critical for safely deploying deep learning models in the real world. Existing approaches for detecting OOD examples work well when ev…