Treister, Eran

26 publications

ICML 2025 Disparate Conditional Prediction in Multiclass Classifiers Sivan Sabato, Eran Treister, Elad Yom-Tov

ICML 2025 Improving the Effective Receptive Field of Message-Passing Neural Networks Shahaf E. Finder, Ron Shapira Weber, Moshe Eliasof, Oren Freifeld, Eran Treister

TMLR 2025 Towards Efficient Training of Graph Neural Networks: A Multiscale Approach Eshed Gal, Moshe Eliasof, Carola-Bibiane Schönlieb, Ivan Kyrchei, Eldad Haber, Eran Treister

ECML-PKDD 2025 Understanding and Improving Laplacian Positional Encodings for Temporal GNNs Yaniv Galron, Fabrizio Frasca, Haggai Maron, Eran Treister, Moshe Eliasof

ECML-PKDD 2025 Zero-Shot Detection of LLM-Generated Code via Approximated Task Conditioning Maor Ashkenazi, Ofir Brenner, Tal Furman Shohet, Eran Treister

ICLRW 2024 Data-Driven Higher Order Differential Equations Inspired Graph Neural Networks Moshe Eliasof, Eldad Haber, Eran Treister, Carola-Bibiane Schönlieb

AISTATS 2024 Efficient Graph Laplacian Estimation by Proximal Newton Yakov Medvedovsky, Eran Treister, Tirza S Routtenberg

AAAI 2024 Feature Transportation Improves Graph Neural Networks Moshe Eliasof, Eldad Haber, Eran Treister

ICLRW 2024 Multigrid-Augmented Deep Learning Preconditioners for the Helmholtz Equation Using Compact Implicit Layers Ido Ben-Yair, Bar Lerer, Eran Treister

AISTATS 2024 On the Temporal Domain of Differential Equation Inspired Graph Neural Networks Moshe Eliasof, Eldad Haber, Eran Treister, Carola-Bibiane B Schönlieb

NeurIPS 2024 Towards Croppable Implicit Neural Representations Maor Ashkenazi, Eran Treister

ECCV 2024 Wavelet Convolutions for Large Receptive Fields Shahaf E Finder, Roy Amoyal, Eran Treister, Oren Freifeld

ICML 2023 Graph Positional Encoding via Random Feature Propagation Moshe Eliasof, Fabrizio Frasca, Beatrice Bevilacqua, Eran Treister, Gal Chechik, Haggai Maron

ICML 2023 Improving Graph Neural Networks with Learnable Propagation Operators Moshe Eliasof, Lars Ruthotto, Eran Treister

ICLR 2023 NeRN: Learning Neural Representations for Neural Networks Maor Ashkenazi, Zohar Rimon, Ron Vainshtein, Shir Levi, Elad Richardson, Pinchas Mintz, Eran Treister

NeurIPSW 2022 PDE-GCN: Novel Architectures for Graph Neural Networks Motivated by Partial Differential Equations Moshe Eliasof, Eldad Haber, Eran Treister

ECCVW 2022 Searching for N:M Fine-Grained Sparsity of Weights and Activations in Neural Networks Ruth Akiva-Hochman, Shahaf E. Finder, Javier S. Turek, Eran Treister

NeurIPS 2022 Wavelet Feature Maps Compression for Image-to-Image CNNs Shahaf E. Finder, Yair Zohav, Maor Ashkenazi, Eran Treister

ICML 2022 pathGCN: Learning General Graph Spatial Operators from Paths Moshe Eliasof, Eldad Haber, Eran Treister

NeurIPSW 2021 MGIC: Multigrid-in-Channels Neural Network Architectures Moshe Eliasof, Jonathan Ephrath, Lars Ruthotto, Eran Treister

NeurIPSW 2021 Multigrid-Augmented Deep Learning Preconditioners for the Helmholtz Equation Yael Azulay, Eran Treister

NeurIPS 2021 PDE-GCN: Novel Architectures for Graph Neural Networks Motivated by Partial Differential Equations Moshe Eliasof, Eldad Haber, Eran Treister

NeurIPSW 2021 Quantized Convolutional Neural Networks Through the Lens of Partial Differential Equations Ido Ben-Yair, Moshe Eliasof, Eran Treister

NeurIPS 2020 DiffGCN: Graph Convolutional Networks via Differential Operators and Algebraic Multigrid Pooling Moshe Eliasof, Eran Treister

ICML 2019 IMEXnet a Forward Stable Deep Neural Network Eldad Haber, Keegan Lensink, Eran Treister, Lars Ruthotto

NeurIPS 2014 A Block-Coordinate Descent Approach for Large-Scale Sparse Inverse Covariance Estimation Eran Treister, Javier S Turek