Uncertainty-aware and explainable machine learning for early prediction of battery degradation trajectory

We present an interpretable uncertainty-aware machine learning model to predict battery degradation trajectories. Using LSTM Recurrent Neural Networks, we reach an RMSE of 106 and MAPE of 10.6%.