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)

Variational Inference Failures Under Model Symmetries: Permutation Invariant Posteriors for Bayesian Neural Networks. - Yoav Gelberg; Tycho F. A. van der Ouderaa; Mark van der Wilk; Yarin Gal (CoRR, 2024)

Learning on LoRAs: GL-Equivariant Processing of Low-Rank Weight Spaces for Large Finetuned Models. - Moe Putterman; Derek Lim; Yoav Gelberg; Stefanie Jegelka; Haggai Maron (CoRR, 2024)

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 (ICLR, 2025)

Learning on LLM Output Signatures for gray-box LLM Behavior Analysis. - Guy Bar-Shalom; Fabrizio Frasca; Derek Lim; Yoav Gelberg; Yftah Ziser; Ran El-Yaniv; Gal Chechik; Haggai Maron (CoRR, 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, 2025)