Tag: Expressivity

All the talks with the tag "Expressivity".

• The Expressive Power of GNNs

  Pankaj Kumar
  Published:Feb 3, 2025 at  at 02:00 PM

  This talk delves into the theoretical foundations of Graph Neural Networks (GNNs), focusing on their ability to model complex relationships between node features and graph structures. While GNNs excel in tasks like node classification and link prediction, their expressive power remains challenging to quantify due to the interplay of graph topology and node features. The discussion highlights key challenges, such as trade-offs between expressiveness and computational efficiency, and explores advancements like the connection between GNNs and the Weisfeiler-Lehman graph isomorphism test. The talk also outlines future directions for developing rigorous evaluation methods to better understand and assess GNN expressivity.