Irregularly-Sampled Time Series Modeling with Spline Networks. (arXiv:2210.10630v1 [cs.LG])

Observations made in continuous time are often irregular and contain the
missing values across different channels. One approach to handle the missing
data is imputing it using splines, by fitting the piecewise polynomials to the
observed values. We propose using the splines as an input to a neural network,
in particular, applying the transformations on the interpolating function
directly, instead of sampling the points on a grid. To do that, we design the
layers that can operate on splines and …

arxiv modeling networks series spline time series