DeepMoD: Deep learning for Model Discovery in noisy data

Understand

We introduce DeepMoD, a Deep learning based Model Discovery algorithm.

• DeepMoD discovers the partial differential equation underlying a spatio-temporal data set using sparse regression on a library of possible functions and their derivatives.
• A neural network approximates the data and constructs the function library, but it also performs the sparse regression.
• This construction makes it extremely robust to noise, applicable to small data sets, and, contrary to other deep learning methods, does not require a training set.