
Haggai Maron
@haggaimaron
Assistant Professor @TechnionLive. Senior research scientist at @nvidia. Learning with group symmetries, graphs and weight spaces.Views do not represent nvidia.
ID: 1020920111476236288
https://haggaim.github.io/ 22-07-2018 06:34:57
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"Balancing Efficiency and Expressiveness: Subgraph GNNs with Walk-Based Centrality" by Josh Southern, Yam Eitan, Guy Bar-Shalom, Michael Bronstein, Haggai Maron, Fabrizio Frasca Paper: arxiv.org/abs/2501.03113 #graphneuralnetworks



Our **Flow Matching Tutorial** from #NeurIPS2024 is now publicly available: neurips.cc/virtual/2024/t… Heli Ben-Hamu Ricky T. Q. Chen

🚀 ICLR 2026 notification, 🚀 #CVPR2025 rebuttal, 🚀 ICML Conference submission - nothing is as fun as submitting a paper to our 🔥 Weight Space Learning Workshop 🔥 at ICLR 2026 Interested? Have a look at: weight-space-learning.github.io Konstantin Schürholt,Giorgos Bouritsas (@[email protected]), Eliahu Horwitz,






📢🔥 If you like to learn about "Proteina", I will be presenting the work in the Machine learning for protein engineering seminar seminar series later today at 1pm PT / 4pm ET. I hope to see you there! 😀


* Graph Learning Will Lose Relevance Due To Poor Benchmarks * Maya Bechler-Speicher, Ben Finkelshtein, Fabrizio Frasca, Luis Muller, et al. Inc. Michael Bronstein Bryan Perozzi Michael Galkin Christopher Morris Wow we should be discussing / acting on this!





📢 Introducing: Learning on LLM Output Signatures for Gray-box LLM Behavior Analysis [arxiv.org/pdf/2503.14043] A joint work with Fabrizio Frasca (co-first author) and our amazing collaborators: Derek Lim Yoav Gelberg Yftah Ziser Ran El-Yaniv Gal Chechik Haggai Maron 🧵Thread



🚨Tutorial on Positional and Structural Graph Representations invariances.org/graph-represen… Given at the National Institute for Theory and Mathematics in Biology. Thanks to Claire Donnat and Olga Klopp for the invitation! Haggai Maron, the tutorial is finally out!