PIVEN: A Deep Neural Network for Prediction Intervals with Specific Value Prediction (2020-06-09T00:00:00.000000Z)

TL;DR

PIVEN is presented, a deep neural network for producing both a PI and a prediction of specific values, and shows that its approach produces tighter uncertainty bounds than the current state-of-the-art approach for producing PIs, while managing to maintain comparable performance to the state of the art approach for specific value-prediction.

Abstract

Improving the robustness of neural nets in regression tasks is key to their application in multiple domains. Deep learning-based approaches aim to achieve this goal either by improving the manner in which they produce their prediction of specific values (i.e., point prediction), or by producing prediction intervals (PIs) that quantify uncertainty. We present PIVEN, a deep neural network for producing both a PI and a prediction of specific values. Benchmark experiments show that our approach produces tighter uncertainty bounds than the current state-of-the-art approach for producing PIs, while managing to maintain comparable performance to the state-of-the-art approach for specific value-prediction. Additional evaluation on large image datasets further support our conclusions.

Authors

L. Rokach

3 papers

Gilad Katz

2 papers

Eli Simhayev

1 papers

TL;DR

Abstract

Authors

References39 items

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