Recent progress in brain-guided image generation has improved the quality of fMRI-based reconstructions; however, fundamental challenges remain in preserving object-level structure …
Graph generation is a crucial task in many fields, including network science and bioinformatics, as it enables the creation of synthetic graphs that mimic the properties of …
Twelve hours of invited teaching for the Computer Science PhD programme on network science, graph neural networks, and graph-learning applications.
Due to their intrinsic capabilities in capturing, modeling, and representing relationships between pieces of information, graphs have been used in a wide variety of application …
Graph Neural Networks (GNNs) have been widely used to learn representations on graphs and tackle many real-world problems from a wide range of domains. In this paper we propose …