Polyhedral Complex

Polyhedral complexes are increasingly used to model and analyze complex systems, particularly in machine learning and computer vision. Current research focuses on efficiently extracting and manipulating these complexes from diverse sources, such as deep neural networks and image data, often employing novel algorithms based on graph representations, conic functions, or edge subdivision techniques. This work aims to improve the accuracy and efficiency of tasks like click-through rate prediction, object recognition, and neural network interpretability, ultimately advancing both theoretical understanding and practical applications of these complex geometric structures. The development of faster and more robust algorithms for polyhedral complex manipulation is a key driver of progress in these fields.