Defining equal input and output shapes for LTC

[mhni-ES]

Hi Liquid AI Team,

I'm reaching out to inquire about the capabilities of the Liquid Time Constant (LTC) network in handling time series data, specifically regarding the output shape consistency with the input shape.

We are currently working with time series data structured as (None, 128, 14, 4). Our objective is to have the LTC network process this data while maintaining the same output shape as the input. However, based on the provided examples, particularly those involving sinusoidal data, it seems that maintaining the input shape in the output might not be possible with LTC.

Could you provide some clarification on this? If maintaining the input shape in the LTC output is feasible, guidance on how to achieve this would be immensely helpful. Any additional information or direction you could offer would be greatly appreciated.