Learning Confidence for Out-of-Distribution Detection in Neural Networks

  title={Learning Confidence for Out-of-Distribution Detection in Neural Networks},
  author={Terrance DeVries and Graham W. Taylor},
Modern neural networks are very powerful predictive models, but they are often incapable of recognizing when their predictions may be wrong. Closely related to this is the task of out-ofdistribution detection, where a network must determine whether or not an input is outside of the set on which it is expected to safely perform. To jointly address these issues, we propose a method of learning confidence estimates for neural networks that is simple to implement and produces intuitively… CONTINUE READING
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