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cs.LG2020★ 39 cited
A Benchmark of Medical Out of Distribution Detection
Tianshi Cao, Chin-Wei Huang, David Yu-Tung Hui +1
Motivation: Deep learning models deployed for use on medical tasks can be equipped with Out-of-Distribution Detection (OoDD) methods in order to avoid erroneous predictions. Howeve…
cs.LG2020
Combating False Negatives in Adversarial Imitation Learning
Konrad Zolna, Chitwan Saharia, Leonard Boussioux +4
In adversarial imitation learning, a discriminator is trained to differentiate agent episodes from expert demonstrations representing the desired behavior. However, as the trained…