TransBoost: Improving the Best ImageNet Performance using Deep Transduction. - Omer Belhasin; Guy Bar-Shalom; Ran El-Yaniv (NeurIPS, 2022)

Distribution Shift Detection for Deep Neural Networks. - Guy Bar-Shalom; Yonatan Geifman; Ran El-Yaniv (CoRR, 2022)

Window-Based Distribution Shift Detection for Deep Neural Networks. - Guy Bar-Shalom; Yonatan Geifman; Ran El-Yaniv (NeurIPS, 2023)

Weakly-supervised Representation Learning for Video Alignment and Analysis. - Guy Bar-Shalom; George Leifman; Michael Elad; Ehud Rivlin (CoRR, 2023)

Subgraphormer: Unifying Subgraph GNNs and Graph Transformers via Graph Products. - Guy Bar-Shalom; Beatrice Bevilacqua; Haggai Maron (ICML, 2024)

A Flexible, Equivariant Framework for Subgraph GNNs via Graph Products and Graph Coarsening. - Guy Bar-Shalom; Yam Eitan; Fabrizio Frasca; Haggai Maron (NeurIPS, 2024)

Weakly-Supervised Representation Learning for Video Alignment and Analysis. - Guy Bar-Shalom; George Leifman; Michael Elad (WACV, 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)

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)

Balancing Efficiency and Expressiveness: Subgraph GNNs with Walk-Based Centrality. - Joshua Southern; Yam Eitan; Guy Bar-Shalom; Michael M. Bronstein; Haggai Maron; Fabrizio Frasca (CoRR, 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)