How can I use variable length inputs to train a regression model?
A quick approach can be using a library like tsfresh, which extracts features from your time series, e.g. max value, number of peaks, median value, etc.

Normally, a thoughtful solution to this kind of problem involves domain knowledge, that is, insights from an expert that can tell you which aspects of your time series are important, e.g. frequent variations, very high peaks, plateaus, local patterns, etc. This knowledge is then used to derive ad hoc feature extractors.