Uncertainty Prediction for Deep Sequential Regression Using Meta Models

2 Jul 2020Jiri NavratilMatthew ArnoldBenjamin Elder

Generating high quality uncertainty estimates for sequential regression, particularly deep recurrent networks, remains a challenging and open problem. Existing approaches often make restrictive assumptions (such as stationarity) yet still perform poorly in practice, particularly in presence of real world non-stationary signals and drift... (read more)

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