Haggai Maron
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
34
Venues
9
Active years
2016–2026
Best venue rank
A*
Where they publish
Papers
34 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2026 | AAAI | Beyond Next Token Probabilities: Learnable, Fast Detection of Hallucinations and Data Contamination on LLM Output Distributions. | Guy Bar-Shalom, Fabrizio Frasca, Derek Lim, Yoav Gelberg, Yftah Ziser, Ran El-Yaniv, Gal Chechik, Haggai Maron |
| 2025 | ICLR | 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 |
| 2025 | ICLR | Homomorphism Expressivity of Spectral Invariant Graph Neural Networks. | Jingchu Gai, Yiheng Du, Bohang Zhang, Haggai Maron, Liwei Wang |
| 2025 | ICLR | Lightning-Fast Image Inversion and Editing for Text-to-Image Diffusion Models. | Dvir Samuel, Barak Meiri, Haggai Maron, Yoad Tewel, Nir Darshan, Shai Avidan, Gal Chechik, Rami Ben-Ari |
| 2025 | ICML | Balancing Efficiency and Expressiveness: Subgraph GNNs with Walk-Based Centrality. | Joshua Southern, Yam Eitan, Guy Bar-Shalom, Michael M. Bronstein, Haggai Maron, Fabrizio Frasca |
| 2024 | ICLR | Efficient Subgraph GNNs by Learning Effective Selection Policies. | Beatrice Bevilacqua, Moshe Eliasof, Eli A. Meirom, Bruno Ribeiro, Haggai Maron |
| 2024 | ICLR | Graph Metanetworks for Processing Diverse Neural Architectures. | Derek Lim, Haggai Maron, Marc T. Law, Jonathan Lorraine, James Lucas |
| 2024 | ICML | Position: Future Directions in the Theory of Graph Machine Learning. | Christopher Morris, Fabrizio Frasca, Nadav Dym, Haggai Maron, Ismail Ilkan Ceylan, Ron Levie, Derek Lim, Michael M. Bronstein, Martin Grohe, Stefanie Jegelka |
| 2024 | ICML | Subgraphormer: Unifying Subgraph GNNs and Graph Transformers via Graph Products. | Guy Bar-Shalom, Beatrice Bevilacqua, Haggai Maron |
| 2024 | ICML | Equivariant Deep Weight Space Alignment. | Aviv Navon, Aviv Shamsian, Ethan Fetaya, Gal Chechik, Nadav Dym, Haggai Maron |
| 2024 | ICML | Improved Generalization of Weight Space Networks via Augmentations. | Aviv Shamsian, Aviv Navon, David W. Zhang, Yan Zhang, Ethan Fetaya, Gal Chechik, Haggai Maron |
| 2024 | ICML | On the Expressive Power of Spectral Invariant Graph Neural Networks. | Bohang Zhang, Lingxiao Zhao, Haggai Maron |
| 2023 | DaWaK | Hierarchical Graph Neural Network with Cross-Attention for Cross-Device User Matching. | Ali Taghibakhshi, Mingyuan Ma, Ashwath Aithal, Onur Yilmaz, Haggai Maron, Matthew West |
| 2023 | ICLR | Sign and Basis Invariant Networks for Spectral Graph Representation Learning. | Derek Lim, Joshua David Robinson, Lingxiao Zhao, Tess E. Smidt, Suvrit Sra, Haggai Maron, Stefanie Jegelka |
| 2023 | ICML | Graph Positional Encoding via Random Feature Propagation. | Moshe Eliasof, Fabrizio Frasca, Beatrice Bevilacqua, Eran Treister, Gal Chechik, Haggai Maron |
| 2023 | ICML | Equivariant Architectures for Learning in Deep Weight Spaces. | Aviv Navon, Aviv Shamsian, Idan Achituve, Ethan Fetaya, Gal Chechik, Haggai Maron |
| 2023 | ICML | Equivariant Polynomials for Graph Neural Networks. | Omri Puny, Derek Lim, Bobak Toussi Kiani, Haggai Maron, Yaron Lipman |
| 2022 | ICLR | Equivariant Subgraph Aggregation Networks. | Beatrice Bevilacqua, Fabrizio Frasca, Derek Lim, Balasubramaniam Srinivasan, Chen Cai, Gopinath Balamurugan, Michael M. Bronstein, Haggai Maron |
| 2022 | ICML | Optimizing Tensor Network Contraction Using Reinforcement Learning. | Eli A. Meirom, Haggai Maron, Shie Mannor, Gal Chechik |
| 2022 | ICML | Multi-Task Learning as a Bargaining Game. | Aviv Navon, Aviv Shamsian, Idan Achituve, Haggai Maron, Kenji Kawaguchi, Gal Chechik, Ethan Fetaya |
| 2021 | ICCV | Deep Permutation Equivariant Structure from Motion. | Dror Moran, Hodaya Koslowsky, Yoni Kasten, Haggai Maron, Meirav Galun, Ronen Basri |
| 2021 | ICLR | On the Universality of Rotation Equivariant Point Cloud Networks. | Nadav Dym, Haggai Maron |
| 2021 | ICLR | Auxiliary Learning by Implicit Differentiation. | Aviv Navon, Idan Achituve, Haggai Maron, Gal Chechik, Ethan Fetaya |
| 2021 | ICML | Controlling Graph Dynamics with Reinforcement Learning and Graph Neural Networks. | Eli A. Meirom, Haggai Maron, Shie Mannor, Gal Chechik |
| 2021 | ICML | From Local Structures to Size Generalization in Graph Neural Networks. | Gilad Yehudai, Ethan Fetaya, Eli A. Meirom, Gal Chechik, Haggai Maron |
| 2021 | IJCAI | On Learning Sets of Symmetric Elements (Extended Abstract). | Haggai Maron, Or Litany, Gal Chechik, Ethan Fetaya |
| 2021 | Interspeech | Scene-Agnostic Multi-Microphone Speech Dereverberation. | Yochai Yemini, Ethan Fetaya, Haggai Maron, Sharon Gannot |
| 2021 | WACV | Self-Supervised Learning for Domain Adaptation on Point Clouds. | Idan Achituve, Haggai Maron, Gal Chechik |
| 2020 | ICML | Learning Algebraic Multigrid Using Graph Neural Networks. | Ilay Luz, Meirav Galun, Haggai Maron, Ronen Basri, Irad Yavneh |
| 2020 | ICML | On Learning Sets of Symmetric Elements. | Haggai Maron, Or Litany, Gal Chechik, Ethan Fetaya |
| 2019 | ICCV | Surface Networks via General Covers. | Niv Haim, Nimrod Segol, Heli Ben-Hamu, Haggai Maron, Yaron Lipman |
| 2019 | ICLR | Invariant and Equivariant Graph Networks. | Haggai Maron, Heli Ben-Hamu, Nadav Shamir, Yaron Lipman |
| 2019 | ICML | On the Universality of Invariant Networks. | Haggai Maron, Ethan Fetaya, Nimrod Segol, Yaron Lipman |
| 2016 | ICCP | Passive light and viewpoint sensitive display of 3D content. | Anat Levin, Haggai Maron, Michal Yarom |