Engineering Uncertainty Estimation in Neural Networks for Time Series Prediction at Uber

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rawwell “There have been various research efforts on approximate inference in deep learning, which we follow to approximate model uncertainty using the Monte Carlo dropout (MC dropout) method.7,8”

2021/05/13 リンク

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Engineering Uncertainty Estimation in Neural Networks for Time Series Prediction at Uber

Data / MLEngineering Uncertainty Estimation in Neural Networks for Time Series Prediction at Uber... Data / MLEngineering Uncertainty Estimation in Neural Networks for Time Series Prediction at UberSeptember 6, 2017 / Global Accurate time series forecasting during high variance segments (e.g., holidays and sporting events) is critical for anomaly detection, resource allocation, budget planning, and other related tasks necessary to facilitate optimal Uber user experiences at scale. Forecasting the