Topological Deep Learning (TDL) is a cutting-edge approach that goes beyond traditional Graph Neural Networks (GNNs) by modeling complex multi-way relationships. TDL has shown superior performance in various machine-learning tasks, but reproducibility, standardization, and benchmarking remain challenges. To address this, researchers have developed TopoBenchmarkX, an open-source library that organizes TDL workflows and transforms graph data into higher-order topological forms. This framework facilitates robust benchmarking and reproducibility in TDL research.
