An implementation of the Legendre Memory Unit (LMU) in jax/flax for time series forecasting. The LMU is a novel memory cell that can be used in recurrent neural networks (RNNs) to process time series data. The LMU is designed to capture long-range dependencies in time series data, and is particularly well-suited for time series forecasting tasks.
The original paper at NeurIPS 2019 can be found here
We use the electric transform temperature prediction dataset from here.
We implement the Legendre Memory Unit (LMU) in jax/flax as described in the original paper. We compare it with the LSTM models provided by the flax library.