Haggai Maron - RankMe

126 papers A* 40A 2B 2Journal 79Unranked 3

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A Graph Meta-Network for Learning on Kolmogorov-Arnold Networks. CoRR Guy Bar-Shalom, Ami Tavory, Itay Evron, Maya Bechler-Speicher, Ido Guy, Haggai Maron
2026	J	`jnl`	A Survey of Weight Space Learning: Understanding, Representation, and Generation. CoRR Xiaolong Han, Zehong Wang, Bo Zhao, Binchi Zhang, Jundong Li, Damian Borth, Rose Yu, Haggai Maron, Yanfang Ye, Lu Yin, Ferrante Neri
2026	A*	`conf`	Beyond Next Token Probabilities: Learnable, Fast Detection of Hallucinations and Data Contamination on LLM Output Distributions. AAAI Guy Bar-Shalom, Fabrizio Frasca, Derek Lim, Yoav Gelberg, Yftah Ziser, Ran El-Yaniv, Gal Chechik, Haggai Maron
2026	J	`jnl`	Learning from Historical Activations in Graph Neural Networks. CoRR Yaniv Galron, Hadar Sinai, Haggai Maron, Moshe Eliasof
2026	J	`jnl`	On the Expressive Power of Permutation-Equivariant Weight-Space Networks. CoRR Adir Dayan, Yam Eitan, Haggai Maron
2026	J	`jnl`	SHINE: A Scalable In-Context Hypernetwork for Mapping Context to LoRA in a Single Pass. CoRR Yewei Liu, Xiyuan Wang, Yansheng Mao, Yoav Gelbery, Haggai Maron, Muhan Zhang
2026	J	`jnl`	Spanning the Visual Analogy Space with a Weight Basis of LoRAs. CoRR Hila Manor, Rinon Gal, Haggai Maron, Tomer Michaeli, Gal Chechik
2025	J	`jnl`	Attention-guided self-supervised distinctive region detection in point clouds. Vis. Comput. Yuval Onn, Haggai Maron, Ayellet Tal
2025	A*	`conf`	Balancing Efficiency and Expressiveness: Subgraph GNNs with Walk-Based Centrality. ICML Joshua Southern, Yam Eitan, Guy Bar-Shalom, Michael M. Bronstein, Haggai Maron, Fabrizio Frasca
2025	J	`jnl`	Balancing Efficiency and Expressiveness: Subgraph GNNs with Walk-Based Centrality. CoRR Joshua Southern, Yam Eitan, Guy Bar-Shalom, Michael M. Bronstein, Haggai Maron, Fabrizio Frasca
2025	J	`jnl`	Beyond Token Probes: Hallucination Detection via Activation Tensors with ACT-ViT. CoRR Guy Bar-Shalom, Fabrizio Frasca, Yaniv Galron, Yftah Ziser, Haggai Maron
2025	J	`jnl`	Directed Graph Generation with Heat Kernels. Trans. Mach. Learn. Res. Marc T. Law, Karsten Kreis, Haggai Maron
2025	J	`jnl`	Efficient GNN Training Through Structure-Aware Randomized Mini-Batching. CoRR Vignesh Balaji, Christos Kozyrakis, Gal Chechik, Haggai Maron
2025	J	`jnl`	FS-KAN: Permutation Equivariant Kolmogorov-Arnold Networks via Function Sharing. CoRR Ran Elbaz, Guy Bar-Shalom, Yam Eitan, Fabrizio Frasca, Haggai Maron
2025	J	`jnl`	Foldable SuperNets: Scalable Merging of Transformers with Different Initializations and Tasks. Trans. Mach. Learn. Res. Edan Kinderman, Itay Hubara, Haggai Maron, Daniel Soudry
2025	J	`jnl`	GradMetaNet: An Equivariant Architecture for Learning on Gradients. CoRR Yoav Gelberg, Yam Eitan, Aviv Navon, Aviv Shamsian, Theo Putterman, Michael M. Bronstein, Haggai Maron
2025	A*	`conf`	Homomorphism Expressivity of Spectral Invariant Graph Neural Networks. ICLR Jingchu Gai, Yiheng Du, Bohang Zhang, Haggai Maron, Liwei Wang
2025	J	`jnl`	Homomorphism Expressivity of Spectral Invariant Graph Neural Networks. CoRR Jingchu Gai, Yiheng Du, Bohang Zhang, Haggai Maron, Liwei Wang
2025	J	`jnl`	It Takes a Graph to Know a Graph: Rewiring for Homophily with a Reference Graph. CoRR Harel Mendelman, Haggai Maron, Ronen Talmon
2025	J	`jnl`	Learning on LLM Output Signatures for gray-box LLM Behavior Analysis. CoRR Guy Bar-Shalom, Fabrizio Frasca, Derek Lim, Yoav Gelberg, Yftah Ziser, Ran El-Yaniv, Gal Chechik, Haggai Maron
2025	A*	`conf`	Lightning-Fast Image Inversion and Editing for Text-to-Image Diffusion Models. ICLR Dvir Samuel, Barak Meiri, Haggai Maron, Yoad Tewel, Nir Darshan, Shai Avidan, Gal Chechik, Rami Ben-Ari
2025	J	`jnl`	Neural Message-Passing on Attention Graphs for Hallucination Detection. CoRR Fabrizio Frasca, Guy Bar-Shalom, Yftah Ziser, Haggai Maron
2025	J	`jnl`	On The Expressive Power of GNN Derivatives. CoRR Yam Eitan, Moshe Eliasof, Yoav Gelberg, Fabrizio Frasca, Guy Bar-Shalom, Haggai Maron
2025	A*	`conf`	Topological Blindspots: Understanding and Extending Topological Deep Learning Through the Lens of Expressivity. ICLR Yam Eitan, Yoav Gelberg, Guy Bar-Shalom, Fabrizio Frasca, Michael M. Bronstein, Haggai Maron
2025	J	`jnl`	Understanding and Improving Laplacian Positional Encodings For Temporal GNNs. CoRR Yaniv Galron, Fabrizio Frasca, Haggai Maron, Eran Treister, Moshe Eliasof
2025	—	`conf`	Understanding and Improving Laplacian Positional Encodings for Temporal GNNs. ECML/PKDD (2) Yaniv Galron, Fabrizio Frasca, Haggai Maron, Eran Treister, Moshe Eliasof
2024	A*	`conf`	A Flexible, Equivariant Framework for Subgraph GNNs via Graph Products and Graph Coarsening. NeurIPS Guy Bar-Shalom, Yam Eitan, Fabrizio Frasca, Haggai Maron
2024	J	`jnl`	A Flexible, Equivariant Framework for Subgraph GNNs via Graph Products and Graph Coarsening. CoRR Guy Bar-Shalom, Yam Eitan, Fabrizio Frasca, Haggai Maron
2024	A*	`conf`	Efficient Subgraph GNNs by Learning Effective Selection Policies. ICLR Beatrice Bevilacqua, Moshe Eliasof, Eli A. Meirom, Bruno Ribeiro, Haggai Maron
2024	A*	`conf`	Equivariant Deep Weight Space Alignment. ICML Aviv Navon, Aviv Shamsian, Ethan Fetaya, Gal Chechik, Nadav Dym, Haggai Maron
2024	A*	`conf`	Fast Encoder-Based 3D from Casual Videos via Point Track Processing. NeurIPS Yoni Kasten, Wuyue Lu, Haggai Maron
2024	J	`jnl`	Foldable SuperNets: Scalable Merging of Transformers with Different Initializations and Tasks. CoRR Edan Kinderman, Itay Hubara, Haggai Maron, Daniel Soudry
2024	J	`jnl`	Future Directions in Foundations of Graph Machine Learning. CoRR Christopher Morris, Nadav Dym, Haggai Maron, Ismail Ilkan Ceylan, Fabrizio Frasca, Ron Levie, Derek Lim, Michael M. Bronstein, Martin Grohe, Stefanie Jegelka
2024	A*	`conf`	GRANOLA: Adaptive Normalization for Graph Neural Networks. NeurIPS Moshe Eliasof, Beatrice Bevilacqua, Carola-Bibiane Schönlieb, Haggai Maron
2024	J	`jnl`	GRANOLA: Adaptive Normalization for Graph Neural Networks. CoRR Moshe Eliasof, Beatrice Bevilacqua, Carola-Bibiane Schönlieb, Haggai Maron
2024	A*	`conf`	Graph Metanetworks for Processing Diverse Neural Architectures. ICLR Derek Lim, Haggai Maron, Marc T. Law, Jonathan Lorraine, James Lucas
2024	A*	`conf`	Improved Generalization of Weight Space Networks via Augmentations. ICML Aviv Shamsian, Aviv Navon, David W. Zhang, Yan Zhang, Ethan Fetaya, Gal Chechik, Haggai Maron
2024	J	`jnl`	Improved Generalization of Weight Space Networks via Augmentations. CoRR Aviv Shamsian, Aviv Navon, David W. Zhang, Yan Zhang, Ethan Fetaya, Gal Chechik, Haggai Maron
2024	J	`jnl`	Learning Priors for Non Rigid SfM from Casual Videos. CoRR Yoni Kasten, Wuyue Lu, Haggai Maron
2024	J	`jnl`	Learning on LoRAs: GL-Equivariant Processing of Low-Rank Weight Spaces for Large Finetuned Models. CoRR Moe Putterman, Derek Lim, Yoav Gelberg, Stefanie Jegelka, Haggai Maron
2024	A*	`conf`	On the Expressive Power of Spectral Invariant Graph Neural Networks. ICML Bohang Zhang, Lingxiao Zhao, Haggai Maron
2024	J	`jnl`	On the Expressive Power of Spectral Invariant Graph Neural Networks. CoRR Bohang Zhang, Lingxiao Zhao, Haggai Maron
2024	J	`jnl`	On the Reconstruction of Training Data from Group Invariant Networks. CoRR Ran Elbaz, Gilad Yehudai, Meirav Galun, Haggai Maron
2024	A*	`conf`	Position: Future Directions in the Theory of Graph Machine Learning. ICML Christopher Morris, Fabrizio Frasca, Nadav Dym, Haggai Maron, Ismail Ilkan Ceylan, Ron Levie, Derek Lim, Michael M. Bronstein, Martin Grohe, Stefanie Jegelka
2024	A*	`conf`	Subgraphormer: Unifying Subgraph GNNs and Graph Transformers via Graph Products. ICML Guy Bar-Shalom, Beatrice Bevilacqua, Haggai Maron
2024	J	`jnl`	Subgraphormer: Unifying Subgraph GNNs and Graph Transformers via Graph Products. CoRR Guy Bar-Shalom, Beatrice Bevilacqua, Haggai Maron
2024	A*	`conf`	The Empirical Impact of Neural Parameter Symmetries, or Lack Thereof. NeurIPS Derek Lim, Theo Putterman, Robin Walters, Haggai Maron, Stefanie Jegelka
2024	J	`jnl`	The Empirical Impact of Neural Parameter Symmetries, or Lack Thereof. CoRR Derek Lim, Moe Putterman, Robin Walters, Haggai Maron, Stefanie Jegelka
2024	J	`jnl`	Topological Blind Spots: Understanding and Extending Topological Deep Learning Through the Lens of Expressivity. CoRR Yam Eitan, Yoav Gelberg, Guy Bar-Shalom, Fabrizio Frasca, Michael M. Bronstein, Haggai Maron
2024	J	`jnl`	Towards Foundation Models on Graphs: An Analysis on Cross-Dataset Transfer of Pretrained GNNs. CoRR Fabrizio Frasca, Fabian Jogl, Moshe Eliasof, Matan Ostrovsky, Carola-Bibiane Schönlieb, Thomas Gärtner, Haggai Maron
2023	J	`jnl`	Data Augmentations in Deep Weight Spaces. CoRR Aviv Shamsian, David W. Zhang, Aviv Navon, Yan Zhang, Miltiadis Kofinas, Idan Achituve, Riccardo Valperga, Gertjan J. Burghouts, Efstratios Gavves, Cees G. M. Snoek, Ethan Fetaya, Gal Chechik, Haggai Maron
2023	J	`jnl`	Efficient Subgraph GNNs by Learning Effective Selection Policies. CoRR Beatrice Bevilacqua, Moshe Eliasof, Eli A. Meirom, Bruno Ribeiro, Haggai Maron
2023	A*	`conf`	Equivariant Architectures for Learning in Deep Weight Spaces. ICML Aviv Navon, Aviv Shamsian, Idan Achituve, Ethan Fetaya, Gal Chechik, Haggai Maron
2023	J	`jnl`	Equivariant Architectures for Learning in Deep Weight Spaces. CoRR Aviv Navon, Aviv Shamsian, Idan Achituve, Ethan Fetaya, Gal Chechik, Haggai Maron
2023	J	`jnl`	Equivariant Deep Weight Space Alignment. CoRR Aviv Navon, Aviv Shamsian, Ethan Fetaya, Gal Chechik, Nadav Dym, Haggai Maron
2023	A*	`conf`	Equivariant Polynomials for Graph Neural Networks. ICML Omri Puny, Derek Lim, Bobak Toussi Kiani, Haggai Maron, Yaron Lipman
2023	J	`jnl`	Equivariant Polynomials for Graph Neural Networks. CoRR Omri Puny, Derek Lim, Bobak Toussi Kiani, Haggai Maron, Yaron Lipman
2023	A*	`conf`	Expressive Sign Equivariant Networks for Spectral Geometric Learning. NeurIPS Derek Lim, Joshua Robinson, Stefanie Jegelka, Haggai Maron
2023	J	`jnl`	Expressive Sign Equivariant Networks for Spectral Geometric Learning. CoRR Derek Lim, Joshua Robinson, Stefanie Jegelka, Haggai Maron
2023	J	`jnl`	Graph Metanetworks for Processing Diverse Neural Architectures. CoRR Derek Lim, Haggai Maron, Marc T. Law, Jonathan Lorraine, James Lucas
2023	A*	`conf`	Graph Positional Encoding via Random Feature Propagation. ICML Moshe Eliasof, Fabrizio Frasca, Beatrice Bevilacqua, Eran Treister, Gal Chechik, Haggai Maron
2023	J	`jnl`	Graph Positional Encoding via Random Feature Propagation. CoRR Moshe Eliasof, Fabrizio Frasca, Beatrice Bevilacqua, Eran Treister, Gal Chechik, Haggai Maron
2023	B	`conf`	Hierarchical Graph Neural Network with Cross-Attention for Cross-Device User Matching. DaWaK Ali Taghibakhshi, Mingyuan Ma, Ashwath Aithal, Onur Yilmaz, Haggai Maron, Matthew West
2023	J	`jnl`	Hierarchical Graph Neural Network with Cross-Attention for Cross-Device User Matching. CoRR Ali Taghibakhshi, Mingyuan Ma, Ashwath Aithal, Onur Yilmaz, Haggai Maron, Matthew West
2023	A*	`conf`	Norm-guided latent space exploration for text-to-image generation. NeurIPS Dvir Samuel, Rami Ben-Ari, Nir Darshan, Haggai Maron, Gal Chechik
2023	J	`jnl`	Norm-guided latent space exploration for text-to-image generation. CoRR Dvir Samuel, Rami Ben-Ari, Nir Darshan, Haggai Maron, Gal Chechik
2023	A*	`conf`	Sign and Basis Invariant Networks for Spectral Graph Representation Learning. ICLR Derek Lim, Joshua David Robinson, Lingxiao Zhao, Tess E. Smidt, Suvrit Sra, Haggai Maron, Stefanie Jegelka
2023	J	`jnl`	Weisfeiler and Leman go Machine Learning: The Story so far. J. Mach. Learn. Res. Christopher Morris, Yaron Lipman, Haggai Maron, Bastian Rieck, Nils M. Kriege, Martin Grohe, Matthias Fey, Karsten M. Borgwardt
2022	—	`conf`	A Simple and Universal Rotation Equivariant Point-Cloud Network. TAG-ML Ben Finkelshtein, Chaim Baskin, Haggai Maron, Nadav Dym
2022	J	`jnl`	A Simple and Universal Rotation Equivariant Point-cloud Network. CoRR Ben Finkelshtein, Chaim Baskin, Haggai Maron, Nadav Dym
2022	A*	`conf`	Equivariant Subgraph Aggregation Networks. ICLR Beatrice Bevilacqua, Fabrizio Frasca, Derek Lim, Balasubramaniam Srinivasan, Chen Cai, Gopinath Balamurugan, Michael M. Bronstein, Haggai Maron
2022	J	`jnl`	Federated Learning with Heterogeneous Architectures using Graph HyperNetworks. CoRR Or Litany, Haggai Maron, David Acuna, Jan Kautz, Gal Chechik, Sanja Fidler
2022	J	`jnl`	Generalized Laplacian Positional Encoding for Graph Representation Learning. CoRR Sohir Maskey, Ali Parviz, Maximilian Thiessen, Hannes Stärk, Ylli Sadikaj, Haggai Maron
2022	A*	`conf`	Multi-Task Learning as a Bargaining Game. ICML Aviv Navon, Aviv Shamsian, Idan Achituve, Haggai Maron, Kenji Kawaguchi, Gal Chechik, Ethan Fetaya
2022	J	`jnl`	Multi-Task Learning as a Bargaining Game. CoRR Aviv Navon, Aviv Shamsian, Idan Achituve, Haggai Maron, Kenji Kawaguchi, Gal Chechik, Ethan Fetaya
2022	A*	`conf`	Optimizing Tensor Network Contraction Using Reinforcement Learning. ICML Eli A. Meirom, Haggai Maron, Shie Mannor, Gal Chechik
2022	J	`jnl`	Optimizing Tensor Network Contraction Using Reinforcement Learning. CoRR Eli A. Meirom, Haggai Maron, Shie Mannor, Gal Chechik
2022	J	`jnl`	Sign and Basis Invariant Networks for Spectral Graph Representation Learning. CoRR Derek Lim, Joshua Robinson, Lingxiao Zhao, Tess E. Smidt, Suvrit Sra, Haggai Maron, Stefanie Jegelka
2022	J	`jnl`	StyleGAN-NADA: CLIP-guided domain adaptation of image generators. ACM Trans. Graph. Rinon Gal, Or Patashnik, Haggai Maron, Amit H. Bermano, Gal Chechik, Daniel Cohen-Or
2022	A*	`conf`	Understanding and Extending Subgraph GNNs by Rethinking Their Symmetries. NeurIPS Fabrizio Frasca, Beatrice Bevilacqua, Michael M. Bronstein, Haggai Maron
2022	J	`jnl`	Understanding and Extending Subgraph GNNs by Rethinking Their Symmetries. CoRR Fabrizio Frasca, Beatrice Bevilacqua, Michael M. Bronstein, Haggai Maron
2021	A*	`conf`	Auxiliary Learning by Implicit Differentiation. ICLR Aviv Navon, Idan Achituve, Haggai Maron, Gal Chechik, Ethan Fetaya
2021	A*	`conf`	Controlling Graph Dynamics with Reinforcement Learning and Graph Neural Networks. ICML Eli A. Meirom, Haggai Maron, Shie Mannor, Gal Chechik
2021	A*	`conf`	Deep Permutation Equivariant Structure from Motion. ICCV Dror Moran, Hodaya Koslowsky, Yoni Kasten, Haggai Maron, Meirav Galun, Ronen Basri
2021	J	`jnl`	Deep Permutation Equivariant Structure from Motion. CoRR Dror Moran, Hodaya Koslowsky, Yoni Kasten, Haggai Maron, Meirav Galun, Ronen Basri
2021	J	`jnl`	Equivariant Subgraph Aggregation Networks. CoRR Beatrice Bevilacqua, Fabrizio Frasca, Derek Lim, Balasubramaniam Srinivasan, Chen Cai, Gopinath Balamurugan, Michael M. Bronstein, Haggai Maron
2021	A*	`conf`	From Local Structures to Size Generalization in Graph Neural Networks. ICML Gilad Yehudai, Ethan Fetaya, Eli A. Meirom, Gal Chechik, Haggai Maron
2021	A*	`conf`	On Learning Sets of Symmetric Elements (Extended Abstract). IJCAI Haggai Maron, Or Litany, Gal Chechik, Ethan Fetaya
2021	A*	`conf`	On the Universality of Rotation Equivariant Point Cloud Networks. ICLR Nadav Dym, Haggai Maron
2021	A	`conf`	Scene-Agnostic Multi-Microphone Speech Dereverberation. Interspeech Yochai Yemini, Ethan Fetaya, Haggai Maron, Sharon Gannot
2021	A	`conf`	Self-Supervised Learning for Domain Adaptation on Point Clouds. WACV Idan Achituve, Haggai Maron, Gal Chechik
2021	J	`jnl`	StyleGAN-NADA: CLIP-Guided Domain Adaptation of Image Generators. CoRR Rinon Gal, Or Patashnik, Haggai Maron, Gal Chechik, Daniel Cohen-Or
2021	J	`jnl`	Weisfeiler and Leman go Machine Learning: The Story so far. CoRR Christopher Morris, Yaron Lipman, Haggai Maron, Bastian Rieck, Nils M. Kriege, Martin Grohe, Matthias Fey, Karsten M. Borgwardt
2020	J	`jnl`	Auxiliary Learning by Implicit Differentiation. CoRR Aviv Navon, Idan Achituve, Haggai Maron, Gal Chechik, Ethan Fetaya
2020	J	`jnl`	How to Stop Epidemics: Controlling Graph Dynamics with Reinforcement Learning and Graph Neural Networks. CoRR Eli A. Meirom, Haggai Maron, Shie Mannor, Gal Chechik
2020	A*	`conf`	Learning Algebraic Multigrid Using Graph Neural Networks. ICML Ilay Luz, Meirav Galun, Haggai Maron, Ronen Basri, Irad Yavneh
2020	J	`jnl`	Learning Algebraic Multigrid Using Graph Neural Networks. CoRR Ilay Luz, Meirav Galun, Haggai Maron, Ronen Basri, Irad Yavneh
2020	A*	`conf`	On Learning Sets of Symmetric Elements. ICML Haggai Maron, Or Litany, Gal Chechik, Ethan Fetaya
2020	J	`jnl`	On Learning Sets of Symmetric Elements. CoRR Haggai Maron, Or Litany, Gal Chechik, Ethan Fetaya
2020	J	`jnl`	On Size Generalization in Graph Neural Networks. CoRR Gilad Yehudai, Ethan Fetaya, Eli A. Meirom, Gal Chechik, Haggai Maron
2020	J	`jnl`	On the Universality of Rotation Equivariant Point Cloud Networks. CoRR Nadav Dym, Haggai Maron
2020	J	`jnl`	Position-Agnostic Multi-Microphone Speech Dereverberation. CoRR Yochai Yemini, Ethan Fetaya, Haggai Maron, Sharon Gannot
2020	J	`jnl`	Self-Supervised Learning for Domain Adaptation on Point-Clouds. CoRR Idan Achituve, Haggai Maron, Gal Chechik
2020	A*	`conf`	Set2Graph: Learning Graphs From Sets. NeurIPS Hadar Serviansky, Nimrod Segol, Jonathan Shlomi, Kyle Cranmer, Eilam Gross, Haggai Maron, Yaron Lipman
2020	J	`jnl`	Set2Graph: Learning Graphs From Sets. CoRR Hadar Serviansky, Nimrod Segol, Jonathan Shlomi, Kyle Cranmer, Eilam Gross, Haggai Maron, Yaron Lipman
2019	A*	`conf`	Controlling Neural Level Sets. NeurIPS Matan Atzmon, Niv Haim, Lior Yariv, Ofer Israelov, Haggai Maron, Yaron Lipman
2019	J	`jnl`	Controlling Neural Level Sets. CoRR Matan Atzmon, Niv Haim, Lior Yariv, Ofer Israelov, Haggai Maron, Yaron Lipman
2019	—	`conf`	Invariant and Equivariant Graph Networks. ICLR (Poster) Haggai Maron, Heli Ben-Hamu, Nadav Shamir, Yaron Lipman
2019	A*	`conf`	On the Universality of Invariant Networks. ICML Haggai Maron, Ethan Fetaya, Nimrod Segol, Yaron Lipman
2019	J	`jnl`	On the Universality of Invariant Networks. CoRR Haggai Maron, Ethan Fetaya, Nimrod Segol, Yaron Lipman
2019	A*	`conf`	Provably Powerful Graph Networks. NeurIPS Haggai Maron, Heli Ben-Hamu, Hadar Serviansky, Yaron Lipman
2019	J	`jnl`	Provably Powerful Graph Networks. CoRR Haggai Maron, Heli Ben-Hamu, Hadar Serviansky, Yaron Lipman
2019	J	`jnl`	Sinkhorn Algorithm for Lifted Assignment Problems. SIAM J. Imaging Sci. Yam Kushinsky, Haggai Maron, Nadav Dym, Yaron Lipman
2019	A*	`conf`	Surface Networks via General Covers. ICCV Niv Haim, Nimrod Segol, Heli Ben-Hamu, Haggai Maron, Yaron Lipman
2018	A*	`conf`	(Probably) Concave Graph Matching. NeurIPS Haggai Maron, Yaron Lipman
2018	J	`jnl`	Invariant and Equivariant Graph Networks. CoRR Haggai Maron, Heli Ben-Hamu, Nadav Shamir, Yaron Lipman
2018	J	`jnl`	Multi-chart Generative Surface Modeling. CoRR Heli Ben-Hamu, Haggai Maron, Itay Kezurer, Gal Avineri, Yaron Lipman
2018	J	`jnl`	Multi-chart generative surface modeling. ACM Trans. Graph. Heli Ben-Hamu, Haggai Maron, Itay Kezurer, Gal Avineri, Yaron Lipman
2018	J	`jnl`	Point Convolutional Neural Networks by Extension Operators. CoRR Matan Atzmon, Haggai Maron, Yaron Lipman
2018	J	`jnl`	Point convolutional neural networks by extension operators. ACM Trans. Graph. Matan Atzmon, Haggai Maron, Yaron Lipman
2018	J	`jnl`	Surface Networks via General Covers. CoRR Niv Haim, Nimrod Segol, Heli Ben-Hamu, Haggai Maron, Yaron Lipman
2017	J	`jnl`	Convolutional neural networks on surfaces via seamless toric covers. ACM Trans. Graph. Haggai Maron, Meirav Galun, Noam Aigerman, Miri Trope, Nadav Dym, Ersin Yumer, Vladimir G. Kim, Yaron Lipman
2017	J	`jnl`	DS++: A flexible, scalable and provably tight relaxation for matching problems. CoRR Nadav Dym, Haggai Maron, Yaron Lipman
2017	J	`jnl`	DS++: a flexible, scalable and provably tight relaxation for matching problems. ACM Trans. Graph. Nadav Dym, Haggai Maron, Yaron Lipman
2016	B	`conf`	Passive light and viewpoint sensitive display of 3D content. ICCP Anat Levin, Haggai Maron, Michal Yarom
2016	J	`jnl`	Point registration via efficient convex relaxation. ACM Trans. Graph. Haggai Maron, Nadav Dym, Itay Kezurer, Shahar Z. Kovalsky, Yaron Lipman