• Better model: in a model-centric approach, the primary emphasis is on creating better algorithms to extract valuable insights from the available data. Lately, especially in the area of Deep Learning, this is mostly done by designing novel architectures. Here, a popular approach is to strengthen the algorithm by tailoring the architecture to the specific application, usually by leveraging symmetries that exist in the data, e.g. crystal structures ; • Better data: in a data-centric approach, the focus is instead on the quality of the inputs for the model. Notable