Yam Eitan

According to our database, Yam Eitan authored at least 8 papers between 2024 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

On the Expressive Power of Permutation-Equivariant Weight-Space Networks.

Adir Dayan, Yam Eitan, Haggai Maron

CoRR, February, 2026

2025

On The Expressive Power of GNN Derivatives.

Yam Eitan, Moshe Eliasof, Yoav Gelberg, Fabrizio Frasca, Guy Bar-Shalom, Haggai Maron

CoRR, October, 2025

FS-KAN: Permutation Equivariant Kolmogorov-Arnold Networks via Function Sharing.

Ran Elbaz, Guy Bar-Shalom, Yam Eitan, Fabrizio Frasca, Haggai Maron

CoRR, September, 2025

GradMetaNet: An Equivariant Architecture for Learning on Gradients.

Yoav Gelberg, Yam Eitan, Aviv Navon, Aviv Shamsian, Theo Putterman, Michael M. Bronstein, Haggai Maron

CoRR, July, 2025

Balancing Efficiency and Expressiveness: Subgraph GNNs with Walk-Based Centrality.

Joshua Southern, Yam Eitan, Guy Bar-Shalom, Michael M. Bronstein, Haggai Maron, Fabrizio Frasca

Proceedings of the Forty-second International Conference on Machine Learning, 2025

Topological Blindspots: Understanding and Extending Topological Deep Learning Through the Lens of Expressivity.

Yam Eitan, Yoav Gelberg, Guy Bar-Shalom, Fabrizio Frasca, Michael M. Bronstein, Haggai Maron

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

Topological Blind Spots: Understanding and Extending Topological Deep Learning Through the Lens of Expressivity.

Yam Eitan, Yoav Gelberg, Guy Bar-Shalom, Fabrizio Frasca, Michael M. Bronstein, Haggai Maron

CoRR, 2024

A Flexible, Equivariant Framework for Subgraph GNNs via Graph Products and Graph Coarsening.

Guy Bar-Shalom, Yam Eitan, Fabrizio Frasca, Haggai Maron

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024