fastmachinelearning/gw-iaas

Support windows for weighted averages on output streaming model

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Some models with output timeseries like DeepClean experience non-trivial drops in predictive performance near the edges of kernels. It would be useful if the output aggregation model in hermes.quiver supported specification of window functions or other weighting schemes to downweight the contributions of predictions made closer to the edge of the kernel.