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Eran Treister

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An Over Complete Deep Learning Method for Inverse Problems

Feb 07, 2024
Moshe Eliasof, Eldad Haber, Eran Treister

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On The Temporal Domain of Differential Equation Inspired Graph Neural Networks

Jan 20, 2024
Moshe Eliasof, Eldad Haber, Eran Treister, Carola-Bibiane Schönlieb

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ADR-GNN: Advection-Diffusion-Reaction Graph Neural Networks

Jul 29, 2023
Moshe Eliasof, Eldad Haber, Eran Treister

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Multigrid-Augmented Deep Learning for the Helmholtz Equation: Better Scalability with Compact Implicit Layers

Jun 30, 2023
Bar Lerer, Ido Ben-Yair, Eran Treister

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DRIP: Deep Regularizers for Inverse Problems

Mar 30, 2023
Moshe Eliasof, Eldad Haber, Eran Treister

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Graph Positional Encoding via Random Feature Propagation

Mar 08, 2023
Moshe Eliasof, Fabrizio Frasca, Beatrice Bevilacqua, Eran Treister, Gal Chechik, Haggai Maron

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Efficient Graph Laplacian Estimation by a Proximal Newton Approach

Feb 13, 2023
Yakov Medvedovsky, Eran Treister, Tirza Routtenberg

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NeRN -- Learning Neural Representations for Neural Networks

Dec 27, 2022
Maor Ashkenazi, Zohar Rimon, Ron Vainshtein, Shir Levi, Elad Richardson, Pinchas Mintz, Eran Treister

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Every Node Counts: Improving the Training of Graph Neural Networks on Node Classification

Nov 29, 2022
Moshe Eliasof, Eldad Haber, Eran Treister

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$ω$GNNs: Deep Graph Neural Networks Enhanced by Multiple Propagation Operators

Oct 31, 2022
Moshe Eliasof, Lars Ruthotto, Eran Treister

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