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Haggai Maron

I am a senior research scientist at NVIDIA Research and a member of NVIDIA's TLV lab. My main fields of interest are machine learning, optimization, and shape analysis. In particular, I am working on applying deep learning to irregular domains (e.g., sets, graphs, point clouds, and surfaces), usually by leveraging their symmetry structure. I completed my Ph.D. in 2019 at the Weizmann Institute of Science under the supervision of Prof. Yaron Lipman.
I will be joining the Faculty of Electrical and Computer Engineering at the Technion as an Assistant Professor in 2023. My CV can be found here.

Email: hmaron (at) nvidia.com, Google scholar page, GitHub page

News

Teaching

  • 2019/spring (WIS): Geometric and Algebraic Methods in Deep Learning
  • 2018/winter (WIS): Geometry and Deep Learning


Publications

Understanding and Extending Subgraph GNNs by Rethinking Their Symmetries

Fabrizio Frasca*, Beatrice Bevilacqua*, Michael M. Bronstein, Haggai Maron
Technical report, May 2022

Abstract Paper

Sign and Basis Invariant Networks for Spectral Graph Representation Learning

Derek Lim*, Joshua Robinson*, Lingxiao Zhao, Tess Smidt, Suvrit Sra, Haggai Maron, Stefanie Jegelka
Technical report, February 2022

Abstract Paper

A Simple and Universal Rotation Equivariant Point-cloud Network

Ben Finkelshtein, Chaim Baskin, Haggai Maron, Nadav Dym
Technical report, February 2022

Abstract Paper

Multi-Task Learning as a Bargaining Game

Aviv Navon, Aviv Shamsian, Idan Achituve, Haggai Maron, Kenji Kawaguchi,Gal Chechik,Ethan Fetaya
International Conference on Machine Learning (ICML) 2022

Abstract Paper

Optimizing Tensor Network Contraction Using Reinforcement Learning

Eli A Meirom, Haggai Maron, Shie Mannor, Gal Chechik
International Conference on Machine Learning (ICML) 2022
Also in The Multi-disciplinary Conference on Reinforcement Learning and Decision Making, RLDM 2022

Abstract Paper

Federated Learning with Heterogeneous Architectures using Graph HyperNetworks

Or Litany, Haggai Maron, David Acuna, Jan Kautz, Gal Chechik, Sanja Fidler
Technical report, January 2022

Abstract Paper

Equivariant Subgraph Aggregation Networks

Beatrice Bevilacqua*, Fabrizio Frasca*, Derek Lim*, Balasubramaniam Srinivasan, Chen Cai, Gopinath Balamurugan, Michael M. Bronstein, Haggai Maron (*equal contribution)
International Conference on Learning Representations (ICLR) 2022

Spotlight presentation (5% acceptance rate)

Abstract Paper GitHub Blog post

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
Technical report, December 2021

Abstract Paper

StyleGAN-NADA: CLIP-Guided Domain Adaptation of Image Generators

Rinon Gal, Or Patashnik , Haggai Maron , Gal Chechik , Daniel Cohen-Or
ACM SIGGRAPH 2022

Abstract Paper Code Interactive demo

Deep Permutation Equivariant Structure from Motion

Dror Moran, Hodaya Koslowsky, Yoni Kasten, Haggai Maron, Meirav Galun, Ronen Basri
International Conference on Computer Vision (ICCV) 2021

Oral presentation (3% acceptance rate)

Abstract Paper Code

Secondary Vertex Finding in Jets with Neural Networks

Jonathan Shlomi, Sanmay Ganguly, Eilam Gross, Kyle Cranmer, Yaron Lipman, Hadar Serviansky, Haggai Maron, Nimrod Segol
European Physical Journal C, 2021

Abstract Paper

Scene-Agnostic Multi-Microphone Speech Dereverberation

Yochai Yemini, Ethan Fetaya, Haggai Maron, Sharon Gannot
INTERSPEECH 2021

Abstract Paper Code

From Local Structures to Size Generalization in Graph Neural Networks

Gilad Yehudai, Ethan Fetaya, Eli Meirom, Gal Chechik, Haggai Maron
International Conference on Machine Learning (ICML) 2021

Abstract Paper

Controlling Graph Dynamics with Reinforcement Learning and Graph Neural Networks

Eli A Meirom, Haggai Maron, Shie Mannor, Gal Chechik
International Conference on Machine Learning (ICML) 2021

Abstract Paper

On the Universality of Rotation Equivariant Point Cloud Networks

Nadav Dym, Haggai Maron
International Conference on Learning Representations (ICLR) 2021

Abstract Paper

Auxiliary Learning by Implicit Differentiation

Aviv Navon*, Idan Achituve*, Haggai Maron, Gal Chechik**, Ethan Fetaya** (*/** equal contribution)
International Conference on Learning Representations (ICLR) 2021

Abstract Paper GitHub

Self-Supervised Learning for Domain Adaptation on Point-Clouds

Idan Achituve, Haggai Maron, Gal Chechik
Winter Conference on Applications of Computer Vision (WACV), 2021

Abstract Paper GitHub

Set2Graph: Learning Graphs From Sets

Hadar Serviansky, Nimrod Segol, Jonathan Shlomi, Kyle Cranmer, Eilam Gross, Haggai Maron, Yaron Lipman
34th Annual Conference on Neural Information Processing Systems (NeurIPS 2020)

Abstract Paper Code

On Learning Sets of Symmetric Elements

Haggai Maron, Or Litany, Gal Chechik, Ethan Fetaya
International Conference on Machine Learning (ICML) 2020

ICML 2020 outstanding paper award

Abstract Paper Code Video Slides Interview

Learning Algebraic Multigrid Using Graph Neural Networks

Ilay Luz, Meirav Galun, Haggai Maron, Ronen Basri, Irad Yavneh
International Conference on Machine Learning (ICML) 2020

Abstract Paper Video+Slides Code

Open Problems: Approximation Power of Invariant Graph Networks

Haggai Maron, Heli Ben-Hamu, Yaron Lipman
NeurIPS 2019 Graph Representation Learning Workshop

Abstract Paper Slides Talk (go to 1:15:00)

Ph.D. Thesis

Haggai Maron
Weizmann Institute of Science, 2019

Abstract Paper

Deep and Convex Shape Analysis

Haggai Maron
SIGGRAPH 2019 Doctoral Consortium

Abstract Paper Poster

Provably Powerful Graph Networks

Haggai Maron*, Heli Ben-Hamu*, Hadar Serviansky*, Yaron Lipman (*equal contribution)
33rd Annual Conference on Neural Information Processing Systems (NeurIPS 2019)

Abstract Arxiv GitHub (TensorFlow) GitHub (PyTorch) Blog post Poster

Controlling Neural Level Sets

Matan Atzmon, Niv Haim, Lior Yariv, Ofer Israelov, Haggai Maron, Yaron Lipman
33rd Annual Conference on Neural Information Processing Systems (NeurIPS 2019)

Abstract Arxiv Code Poster

Surface Networks via General Covers

Niv Haim*, Nimrod Segol*, Heli Ben-Hamu, Haggai Maron, Yaron Lipman (*equal contribution)
International Conference on Computer Vision (ICCV) 2019

Abstract Arxiv

On the Universality of Invariant Networks

Haggai Maron, Ethan Fetaya, Nimrod Segol, Yaron Lipman
International Conference on Machine Learning (ICML) 2019

Abstract Arxiv Poster Video Blog post
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Invariant and Equivariant Graph Networks

Haggai Maron, Heli Ben-Hamu, Nadav Shamir and Yaron Lipman
International Conference on Learning Representations (ICLR) 2019

Abstract Arxiv GitHub Poster Blog post
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Sinkhorn Algorithm for Lifted Assignment Problems

Yam Kushinsky, Haggai Maron, Nadav Dym and Yaron Lipman
SIAM Journal on Imaging Sciences, 2019

Abstract Arxiv
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(Probably) Concave Graph Matching

Haggai Maron and Yaron Lipman
32nd Annual Conference on Neural Information Processing Systems (NeurIPS 2018)

spotlight presentation (3.5% acceptance rate)

Abstract Arxiv Poster Short Video GitHub
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Multi-chart Generative Surface Modeling

Heli Ben-Hamu, Haggai Maron, Itay Kezurer, Gal Avineri and Yaron Lipman
ACM SIGGRAPH Asia 2018

Abstract Arxiv GitHub
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Point Convolutional Neural Networks by Extension Operators

Matan Atzmon*, Haggai Maron* and Yaron Lipman (*equal contribution)
ACM SIGGRAPH 2018

Abstract Arxiv GitHub Slides
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DS++: A Flexible, Scalable and Provably Tight Relaxation for Matching Problems

Nadav Dym*, Haggai Maron* and Yaron Lipman (*equal contribution)
ACM SIGGRAPH ASIA 2017

Abstract Arxiv GitHub Slides
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Convolutional Neural Networks on Surfaces via Seamless Toric Covers

Haggai Maron, Meirav Galun, Noam Aigerman, Miri Trope, Nadav Dym, Ersin Yumer, Vladimir G. Kim and Yaron Lipman
ACM SIGGRAPH 2017

Abstract Paper (low res) GitHub Data Slides Video
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Point Registration via Efficient Convex Relaxation

Haggai Maron, Nadav Dym, Itay Kezurer, Shahar Kovalsky and Yaron Lipman
ACM SIGGRAPH 2016

Abstract Paper (low res) GitHub Slides Video
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Passive Light and Viewpoint Sensitive Display of 3D Content

Anat Levin, Haggai Maron and Michal Yarom
International Conference on Computational Photography (ICCP) 2016

Abstract Paper Paper+Supplementary