Forecasting emissions through Kaya identity using Neural Ordinary Differential Equations. (arXiv:2201.02433v1 [cs.LG])

Starting from the Kaya identity, we used a Neural ODE model to predict the
evolution of several indicators related to carbon emissions, on a
country-level: population, GDP per capita, energy intensity of GDP, carbon
intensity of energy. We compared the model with a baseline statistical model -
VAR - and obtained good performances. We conclude that this machine-learning
approach can be used to produce a wide range of results and give relevant
insight to policymakers

arxiv forecasting identity ordinary