A research team from the Skoltech AI Center proposed a new neural network architecture for generating structured curved coordinate grids, an important tool for calculations in physics, biology, and even finance. The study is published in the Scientific Reports journal.

“Building a coordinate grid is a key task for modeling. Breaking down a complex space into manageable pieces is necessary, as it allows you to accurately determine the changes in different quantities—temperature, speed, pressure, and so on,” commented the lead author of the paper, Bari Khairullin, a Ph.D. student from the Computational and Data Science and Engineering program at Skoltech.

“Without a good grid, calculations become either inaccurate or impossible. In physics, they help model the movement of liquids and gases, in biology, tissue growth and drug distribution, and in finance, they predict market fluctuations. The proposed approach opens up new possibilities in building grids using artificial intelligence.”