2 papers
cs.LG2026
Grasynda: Graph-based Synthetic Time Series Generation
Luis Amorim, Moises Santos, Paulo J. Azevedo +2
Data augmentation is a crucial tool in time series forecasting, especially for deep learning architectures that require a large training sample size to generalize effectively. Howe…
cs.SI2025
Generating Large Semi-Synthetic Graphs of Any Size
Rodrigo Tuna, Carlos Soares
Graph generation is an important area in network science. Traditional approaches focus on replicating specific properties of real-world graphs, such as small diameters or power-law…