Spherical Surface

Spherical surface research focuses on developing efficient and accurate methods for representing, analyzing, and processing data defined on spheres, a geometry prevalent in numerous scientific domains. Current research emphasizes novel algorithms for data fitting and interpolation on spherical surfaces, often leveraging techniques like spherical harmonics, convolutional neural networks tailored for spherical geometries (e.g., Spherical FNOs, HEAL-SWIN), and factorized attention mechanisms. These advancements are crucial for improving accuracy and efficiency in diverse applications, including weather forecasting, brain imaging analysis, and 3D object reconstruction, where spherical representations are essential.