Collocation Point

Collocation points are strategically chosen locations within a problem domain used to approximate solutions in various scientific fields. Current research focuses on optimizing their selection and distribution, particularly within Physics-Informed Neural Networks (PINNs) and other data-driven models, employing techniques like adaptive sampling and curriculum training to improve accuracy and efficiency. These advancements are impacting diverse areas, from solving complex partial differential equations and inferring stochastic dynamics to enhancing robotic control and improving remote sensing data analysis. The ultimate goal is to achieve more accurate and computationally efficient solutions across a range of scientific and engineering problems.