Maron, Haggai

60 publications

ICML 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

NeurIPS 2025 Beyond Token Probes: Hallucination Detection via Activation Tensors with ACT-ViT Guy Bar-Shalom, Fabrizio Frasca, Yaniv Galron, Yftah Ziser, Haggai Maron

TMLR 2025 Directed Graph Generation with Heat Kernels Marc T. Law, Karsten Kreis, Haggai Maron

TMLR 2025 Foldable SuperNets: Scalable Merging of Transformers with Different Initializations and Tasks Edan Kinderman, Itay Hubara, Haggai Maron, Daniel Soudry

NeurIPS 2025 GradMetaNet: An Equivariant Architecture for Learning on Gradients Yoav Gelberg, Yam Eitan, Aviv Navon, Aviv Shamsian, Theo Putterman, Michael M. Bronstein, Haggai Maron

ICLRW 2025 GradMetaNet: An Equivariant Architecture for Learning on Gradients Yoav Gelberg, Yam Eitan, Aviv Navon, Aviv Shamsian, Theo Putterman, Haggai Maron

ICLR 2025 Homomorphism Expressivity of Spectral Invariant Graph Neural Networks Jingchu Gai, Yiheng Du, Bohang Zhang, Haggai Maron, Liwei Wang

ICLRW 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

ICLRW 2025 Learning on LoRAs: GL-Equivariant Processing of Low-Rank Weight Spaces for Large Finetuned Models Theo Putterman, Derek Lim, Yoav Gelberg, Stefanie Jegelka, Haggai Maron

ICLR 2025 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

ICLR 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

ECML-PKDD 2025 Understanding and Improving Laplacian Positional Encodings for Temporal GNNs Yaniv Galron, Fabrizio Frasca, Haggai Maron, Eran Treister, Moshe Eliasof

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

ICLR 2024 Efficient Subgraph GNNs by Learning Effective Selection Policies Beatrice Bevilacqua, Moshe Eliasof, Eli Meirom, Bruno Ribeiro, Haggai Maron

NeurIPSW 2024 Efficient Subgraph GNNs via Graph Products and Coarsening Guy Bar-Shalom, Yam Eitan, Fabrizio Frasca, Haggai Maron

ICML 2024 Equivariant Deep Weight Space Alignment Aviv Navon, Aviv Shamsian, Ethan Fetaya, Gal Chechik, Nadav Dym, Haggai Maron

NeurIPS 2024 Fast Encoder-Based 3D from Casual Videos via Point Track Processing Yoni Kasten, Wuyue Lu, Haggai Maron

NeurIPS 2024 GRANOLA: Adaptive Normalization for Graph Neural Networks Moshe Eliasof, Beatrice Bevilacqua, Carola-Bibiane Schönlieb, Haggai Maron

ICLR 2024 Graph Metanetworks for Processing Diverse Neural Architectures Derek Lim, Haggai Maron, Marc T. Law, Jonathan Lorraine, James Lucas

ICML 2024 Improved Generalization of Weight Space Networks via Augmentations Aviv Shamsian, Aviv Navon, David W. Zhang, Yan Zhang, Ethan Fetaya, Gal Chechik, Haggai Maron

ICML 2024 On the Expressive Power of Spectral Invariant Graph Neural Networks Bohang Zhang, Lingxiao Zhao, Haggai Maron

NeurIPSW 2024 On the Reconstruction of Training Data from Group Invariant Networks Ran Elbaz, Gilad Yehudai, Meirav Galun, Haggai Maron

ICML 2024 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

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

NeurIPS 2024 The Empirical Impact of Neural Parameter Symmetries, or Lack Thereof Derek Lim, Theo Putterman, Robin Walters, Haggai Maron, Stefanie Jegelka

ICMLW 2024 The Empirical Impact of Neural Parameter Symmetries, or Lack Thereof Derek Lim, Theo Putterman, Robin Walters, Haggai Maron, Stefanie Jegelka

NeurIPSW 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

NeurIPSW 2024 Towards Foundation Models on Graphs: An Analysis on Cross-Dataset Transfer of Pretrained GNNs Fabrizio Frasca, Fabian Jogl, Moshe Eliasof, Matan Ostrovsky, Carola-Bibiane Schönlieb, Thomas Gärtner, Haggai Maron

NeurIPSW 2023 Data Augmentations in Deep Weight Spaces Aviv Shamsian, David Zhang, Aviv Navon, Yan Zhang, Miltiadis Kofinas, Idan Achituve, Riccardo Valperga, Gertjan Burghouts, Efstratios Gavves, Cees Snoek, Ethan Fetaya, Gal Chechik, Haggai Maron

ICML 2023 Equivariant Architectures for Learning in Deep Weight Spaces Aviv Navon, Aviv Shamsian, Idan Achituve, Ethan Fetaya, Gal Chechik, Haggai Maron

ICML 2023 Equivariant Polynomials for Graph Neural Networks Omri Puny, Derek Lim, Bobak Kiani, Haggai Maron, Yaron Lipman

NeurIPS 2023 Expressive Sign Equivariant Networks for Spectral Geometric Learning Derek Lim, Joshua W. Robinson, Stefanie Jegelka, Haggai Maron

ICLRW 2023 Expressive Sign Equivariant Networks for Spectral Geometric Learning Derek Lim, Joshua Robinson, Stefanie Jegelka, Yaron Lipman, Haggai Maron

ICMLW 2023 Expressive Sign Equivariant Networks for Spectral Geometric Learning Derek Lim, Joshua Robinson, Stefanie Jegelka, Haggai Maron

ICML 2023 Graph Positional Encoding via Random Feature Propagation Moshe Eliasof, Fabrizio Frasca, Beatrice Bevilacqua, Eran Treister, Gal Chechik, Haggai Maron

NeurIPS 2023 Norm-Guided Latent Space Exploration for Text-to-Image Generation Dvir Samuel, Rami Ben-Ari, Nir Darshan, Haggai Maron, Gal Chechik

ICLR 2023 Sign and Basis Invariant Networks for Spectral Graph Representation Learning Derek Lim, Joshua David Robinson, Lingxiao Zhao, Tess Smidt, Suvrit Sra, Haggai Maron, Stefanie Jegelka

NeurIPSW 2023 Subgraphormer: Subgraph GNNs Meet Graph Transformers Guy Bar-Shalom, Beatrice Bevilacqua, Haggai Maron

JMLR 2023 Weisfeiler and Leman Go Machine Learning: The Story so Far Christopher Morris, Yaron Lipman, Haggai Maron, Bastian Rieck, Nils M. Kriege, Martin Grohe, Matthias Fey, Karsten Borgwardt

ICLR 2022 Equivariant Subgraph Aggregation Networks Beatrice Bevilacqua, Fabrizio Frasca, Derek Lim, Balasubramaniam Srinivasan, Chen Cai, Gopinath Balamurugan, Michael M. Bronstein, Haggai Maron

NeurIPSW 2022 Generalized Laplacian Positional Encoding for Graph Representation Learning Sohir Maskey, Ali Parviz, Maximilian Thiessen, Hannes Stärk, Ylli Sadikaj, Haggai Maron

ICML 2022 Multi-Task Learning as a Bargaining Game Aviv Navon, Aviv Shamsian, Idan Achituve, Haggai Maron, Kenji Kawaguchi, Gal Chechik, Ethan Fetaya

ICML 2022 Optimizing Tensor Network Contraction Using Reinforcement Learning Eli Meirom, Haggai Maron, Shie Mannor, Gal Chechik

ICLRW 2022 Sign and Basis Invariant Networks for Spectral Graph Representation Learning Derek Lim, Joshua David Robinson, Lingxiao Zhao, Tess Smidt, Suvrit Sra, Haggai Maron, Stefanie Jegelka

NeurIPS 2022 Understanding and Extending Subgraph GNNs by Rethinking Their Symmetries Fabrizio Frasca, Beatrice Bevilacqua, Michael Bronstein, Haggai Maron

ICLR 2021 Auxiliary Learning by Implicit Differentiation Aviv Navon, Idan Achituve, Haggai Maron, Gal Chechik, Ethan Fetaya

ICML 2021 Controlling Graph Dynamics with Reinforcement Learning and Graph Neural Networks Eli Meirom, Haggai Maron, Shie Mannor, Gal Chechik

ICCV 2021 Deep Permutation Equivariant Structure from Motion Dror Moran, Hodaya Koslowsky, Yoni Kasten, Haggai Maron, Meirav Galun, Ronen Basri

ICML 2021 From Local Structures to Size Generalization in Graph Neural Networks Gilad Yehudai, Ethan Fetaya, Eli Meirom, Gal Chechik, Haggai Maron

IJCAI 2021 On Learning Sets of Symmetric Elements (Extended Abstract) Haggai Maron, Or Litany, Gal Chechik, Ethan Fetaya

ICLR 2021 On the Universality of Rotation Equivariant Point Cloud Networks Nadav Dym, Haggai Maron

WACV 2021 Self-Supervised Learning for Domain Adaptation on Point Clouds Idan Achituve, Haggai Maron, Gal Chechik

ICML 2020 Learning Algebraic Multigrid Using Graph Neural Networks Ilay Luz, Meirav Galun, Haggai Maron, Ronen Basri, Irad Yavneh

ICML 2020 On Learning Sets of Symmetric Elements Haggai Maron, Or Litany, Gal Chechik, Ethan Fetaya

NeurIPS 2020 Set2Graph: Learning Graphs from Sets Hadar Serviansky, Nimrod Segol, Jonathan Shlomi, Kyle Cranmer, Eilam Gross, Haggai Maron, Yaron Lipman

NeurIPS 2019 Controlling Neural Level Sets Matan Atzmon, Niv Haim, Lior Yariv, Ofer Israelov, Haggai Maron, Yaron Lipman

ICLR 2019 Invariant and Equivariant Graph Networks Haggai Maron, Heli Ben-Hamu, Nadav Shamir, Yaron Lipman

ICML 2019 On the Universality of Invariant Networks Haggai Maron, Ethan Fetaya, Nimrod Segol, Yaron Lipman

NeurIPS 2019 Provably Powerful Graph Networks Haggai Maron, Heli Ben-Hamu, Hadar Serviansky, Yaron Lipman

NeurIPS 2018 (Probably) Concave Graph Matching Haggai Maron, Yaron Lipman