# Spline Layer

Constructs a Spline Layer. At a high-level, it performs the following:

1. Takes as input a one-dimensional training dataset, a time span, a time step and an interpolation method.
2. During training, adjusts the values of the function at multiples of the time-step such that the curve interpolated through these points has minimum loss on the corresponding one-dimensional dataset.
DiffEqFlux.SplineLayerType

Constructs a Spline Layer. At a high-level, it performs the following:

1. Takes as input a one-dimensional training dataset, a time span, a time step and

an interpolation method.

1. During training, adjusts the values of the function at multiples of the time-step

such that the curve interpolated through these points has minimum loss on the corresponding one-dimensional dataset.

SplineLayer(time_span,time_step,spline_basis,saved_points=nothing)

Arguments:

• time_span: Tuple of real numbers corresponding to the time span.
• time_step: Real number corresponding to the time step.
• spline_basis: Interpolation method to be used yb the basis (current supported interpolation methods: ConstantInterpolation, LinearInterpolation, QuadraticInterpolation, QuadraticSpline, CubicSpline).
• 'saved_points': values of the function at multiples of the time step. Initialized by default

to a random vector sampled from the unit normal.