Method and system for performing time series imputation

A computing apparatus for performing time series imputation, the computing apparatus comprising:

• a processor;
• a memory;
• and
• a communication interface coupled to each of the processor and the memory,
• wherein the processor is configured to:
• receive, via the communication interface, first information that relates to a latent vector representation of a first time series for which at least one value is missing;
• generate, based on the first information, a set of network weights that is usable by a sinusoidal representation network model for obtaining a functional representation of the first time series;
• modulate, based on the first information, a set of sine activation amplitudes of the functional representation of the first time series;
• and
• impute, based on the set of network weights and a result of the modulation, the at least one missing value of the first time series.

A non-transitory computer readable storage medium storing instructions for performing time series imputation, the storage medium comprising executable code which, when executed by a processor, causes the processor to:

• receive first information that relates to a latent vector representation of a first time series for which at least one value is missing;
• generate, based on the first information, a set of network weights that is usable by a sinusoidal representation network model for obtaining a functional representation of the first time series;
• modulate, based on the first information, a set of sine activation amplitudes of the functional representation of the first time series;
• and
• impute, based on the set of network weights and a result of the modulation, the at least one missing value of the first time series.