Haggai Maron

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Yaron LipmanWeizmann Institute, FAIR MetaDirección de correo verificada de weizmann.ac.il
Gal ChechikNVIDIA, Bar Ilan UniversityDirección de correo verificada de biu.ac.il
Ethan FetayaBar-Ilan UniversityDirección de correo verificada de biu.ac.il
nadav dymSenior Lecturer at TechnionDirección de correo verificada de technion.ac.il
Heli Ben-HamuPh.D. student, Weizmann Institute of ScienceDirección de correo verificada de weizmann.ac.il
Derek LimMITDirección de correo verificada de mit.edu
Beatrice BevilacquaPhD Candidate, Purdue UniversityDirección de correo verificada de purdue.edu
Fabrizio FrascaPosdoctoral Fellow, Technion – Israel Institute of TechnologyDirección de correo verificada de ic.ac.uk
Matan AtzmonResearch Scientist, NVIDIADirección de correo verificada de nvidia.com
Idan AchituveBar-Ilan UniversityDirección de correo verificada de biu.ac.il
Eli MeiromTechion - Israel Institute of TechnologyDirección de correo verificada de tx.technion.ac.il
Aviv NavonBar-Ilan UniversityDirección de correo verificada de biu.ac.il
Michael BronsteinDeepMind Professor of AI, University of Oxford / Scientific Director, AITHYRADirección de correo verificada de cs.ox.ac.uk
meirav galunDr of Applied Math and Computer Science, Weizmann InstituteDirección de correo verificada de weizmann.ac.il
Stefanie JegelkaTUM and MITDirección de correo verificada de mit.edu
Aviv ShamsianPhD Candidate Bar Ilan UniversityDirección de correo verificada de live.biu.ac.il
Or LitanyTechnion, NVIDIADirección de correo verificada de nvidia.com
Rinon GalTel Aviv UniversityDirección de correo verificada de mail.tau.ac.il
Martin GroheProfessor of Computer Science, RWTH Aachen UniversityDirección de correo verificada de informatik.rwth-aachen.de
Christopher MorrisRWTH Aachen UniversityDirección de correo verificada de cs.rwth-aachen.de

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Haggai Maron

Assistant Professor at the Technion, Research Scientist at NVIDIA Research

Dirección de correo verificada de technion.ac.il - Página principal

Graph Neural Networks Geometric Deep Learning Deep Learning Equivariant Architectures


Título Ordenar por citas Ordenar por año Ordenar por título	Citado por Citado por	Año
Provably Powerful Graph Networks H Maron, H Ben-Hamu, H Serviansky*, Y Lipman Advances in Neural Information Processing Systems, 2019	642	2019
Stylegan-nada: Clip-guided domain adaptation of image generators R Gal, O Patashnik, H Maron, AH Bermano, G Chechik, D Cohen-Or ACM Transactions on Graphics (TOG) 41 (4), 1-13, 2022	615	2022
Point convolutional neural networks by extension operators M Atzmon, H Maron, Y Lipman SIGGRAPH 2018, 2018	602	2018
Invariant and Equivariant Graph Networks H Maron, H Ben-Hamu, N Shamir, Y Lipman International Conference on Learning Representations (ICLR), 2019	536	2019
Convolutional neural networks on surfaces via seamless toric covers H Maron, M Galun, N Aigerman, M Trope, N Dym, E Yumer, VG Kim, ... ACM Trans. Graph 36 (4), 71, 2017	264	2017
On the Universality of Invariant Networks H Maron, E Fetaya, N Segol, Y Lipman International Conference on Machine Learning (ICML), 2019	260	2019
Equivariant subgraph aggregation networks B Bevilacqua, F Frasca, D Lim, B Srinivasan, C Cai, G Balamurugan, ... International Conference on Learning Representations (ICLR) 2022 (Spotlight), 2022	197	2022
Self-Supervised Learning for Domain Adaptation on Point-Clouds I Achituve, H Maron, G Chechik Winter Conference on Applications of Computer Vision (WACV), 2021, 2021	187	2021
Point registration via efficient convex relaxation H Maron, N Dym, I Kezurer, S Kovalsky, Y Lipman ACM Transactions on Graphics (TOG) 35 (4), 73, 2016	160	2016
Sign and basis invariant networks for spectral graph representation learning D Lim, J Robinson, L Zhao, T Smidt, S Sra, H Maron, S Jegelka arXiv preprint arXiv:2202.13013, 2022	151	2022
From Local Structures to Size Generalization in Graph Neural Networks G Yehudai, E Fetaya, E Meirom, G Chechik, H Maron International Conference on Machine Learning (ICML) 2021, 2021	141*	2021
On Learning Sets of Symmetric Elements H Maron, O Litany, G Chechik, E Fetaya International Conference on Machine Learning (ICML 2020), Outstanding paper …, 2020	137	2020
Understanding and extending subgraph gnns by rethinking their symmetries F Frasca, B Bevilacqua, MM Bronstein, H Maron Advances in Neural Information Processing Systems 2022 (Oral), 2022	133	2022
Weisfeiler and leman go machine learning: The story so far C Morris, Y Lipman, H Maron, B Rieck, NM Kriege, M Grohe, M Fey, ... The Journal of Machine Learning Research 24 (1), 15865-15923, 2023	128	2023
Controlling Neural Level Sets M Atzmon, N Haim, L Yariv, O Israelov, H Maron, Y Lipman Advances in Neural Information Processing Systems, 2019	125	2019
Multi-task learning as a bargaining game A Navon, A Shamsian, I Achituve, H Maron, K Kawaguchi, G Chechik, ... International Conference on Machine Learning (ICML) 2022, 2022	117	2022
On the Universality of Rotation Equivariant Point Cloud Networks N Dym, H Maron International Conference on Learning Representations (ICLR) 2021, 2021	92	2021
Multi-chart generative surface modeling H Ben-Hamu, H Maron, I Kezurer, G Avineri, Y Lipman SIGGRAPH Asia 2018 Technical Papers, 215, 2018	87	2018
Learning Algebraic Multigrid Using Graph Neural Networks I Luz, M Galun, H Maron, R Basri, I Yavneh International Conference on Machine Learning (ICML 2020), 2020	83	2020
DS++: A flexible, scalable and provably tight relaxation for matching problems N Dym, H Maron, Y Lipman ACM Transactions on Graphics (TOG) 36 (6), 184:1--184:14, 2017	82	2017

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