Partial differential equations provide accurate models for many physical processes, although
their derivation can be challenging, requiring a fundamental understanding of the modeled …

Predicting the spatiotemporal data of natural processes is crucial for both academic
research and industrial applications. In particular, ice formation and melting processes play …

The discovery of equations with knowledge of the process origin is a tempting prospect.
However, most equation discovery tools rely on gradient methods, which offer limited control …

Differential equation discovery, a machine learning subfield, is used to develop interpretable
models, particularly in nature-related applications. By expertly incorporating the general …

Evolutionary differential equation discovery proved to be a tool to obtain equations with less
a priori assumptions than conventional approaches, such as sparse symbolic regression …

In a wide range of applications, heating or cooling systems provide not only temperature
changes, but also small temperature gradients in a sample or industrial facility. Although a …

The natural world is known to consistently abide by scientific laws that can be expressed
concisely in mathematical terms, including differential equations. To understand the patterns …