haggaim.github.io - Haggai's Homepage

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I am a senior research scientist at NVIDIA Research and a member of NVIDIA's TLV lab . I am also an incoming Assistant Professor at the Faculty of Electrical and Computer Engineering at the Technion . My main field of interest is machine learning. In particular, I am working on applying deep learning to structured 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

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

News I will serve as an area chair at NeurIPS 2023. A recent podcast with me on graph neural networks (hebrew) See our recent tutorial on Exploring the practical and theoretical landscape of expressive graph neural networks given at the Learning on Graphs Conference . With With Fabrizio Frasca and Beatrice Bevilacqua. See my recent talk on Subgraph-based networks for expressive, efficient, and domain-independent graph learning at the Signal Processing and Machine Learning on Graphs hosted by CIRM . Our pape

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