# Discovering dependencies in complex physical systems using Neural Networks

arXiv: https://arxiv.org/abs/2101.12583 · HTML: https://mlsanity.com/paper/2101.12583/

## Key facts

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- First posted on arXiv 27 Jan 2021.

## Abstract (arXiv)

In todays age of data, discovering relationships between different variables is an interesting and a challenging problem. This problem becomes even more critical with regards to complex dynamical systems like weather forecasting and econometric models, which can show highly non-linear behavior. A method based on mutual information and deep neural networks is proposed as a versatile framework for discovering non-linear relationships ranging from functional dependencies to causality. We demonstrate the application of this method to actual multivariable non-linear dynamical systems. We also show that this method can find relationships even for datasets with small number of datapoints, as is often the case with empirical data.