Eliasof, Moshe

29 publications

CVPR 2025 DiTASK: Multi-Task Fine-Tuning with Diffeomorphic Transformations Krishna Sri Ipsit Mantri, Carola-Bibiane Schönlieb, Bruno Ribeiro, Chaim Baskin, Moshe Eliasof

ICLR 2025 Estimation of Single-Cell and Tissue Perturbation Effect in Spatial Transcriptomics via Spatial Causal Disentanglement Stathis Megas, Daniel G. Chen, Krzysztof Polanski, Moshe Eliasof, Carola-Bibiane Schönlieb, Sarah A Teichmann

ICML 2025 Graph Adaptive Autoregressive Moving Average Models Moshe Eliasof, Alessio Gravina, Andrea Ceni, Claudio Gallicchio, Davide Bacciu, Carola-Bibiane Schönlieb

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

AAAI 2025 Learning Regularization for Graph Inverse Problems Moshe Eliasof, Md Shahriar Rahim Siddiqui, Carola-Bibiane Schönlieb, Eldad Haber

AAAI 2025 On Oversquashing in Graph Neural Networks Through the Lens of Dynamical Systems Alessio Gravina, Moshe Eliasof, Claudio Gallicchio, Davide Bacciu, Carola-Bibiane Schönlieb

NeurIPS 2025 One-Step Offline Distillation of Diffusion-Based Models via Koopman Modeling Nimrod Berman, Ilan Naiman, Moshe Eliasof, Hedi Zisling, Omri Azencot

NeurIPS 2025 Return of ChebNet: Understanding and Improving an Overlooked GNN on Long Range Tasks Ali Hariri, Alvaro Arroyo, Alessio Gravina, Moshe Eliasof, Carola-Bibiane Schönlieb, Davide Bacciu, Xiaowen Dong, Kamyar Azizzadenesheli, Pierre Vandergheynst

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

TMLR 2025 Towards Graph Foundation Models: A Study on the Generalization of Positional and Structural Encodings Billy Joe Franks, Moshe Eliasof, Semih Cantürk, Guy Wolf, Carola-Bibiane Schönlieb, Sophie Fellenz, Marius Kloft

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

NeurIPS 2024 Advection Augmented Convolutional Neural Networks Niloufar Zakariaei, Siddharth Rout, Eldad Haber, Moshe Eliasof

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

NeurIPS 2024 DiGRAF: Diffeomorphic Graph-Adaptive Activation Function Krishna Sri Ipsit Mantri, Xinzhi Wang, Carola-Bibiane Schönlieb, Bruno Ribeiro, Beatrice Bevilacqua, Moshe Eliasof

ICLR 2024 Efficient Subgraph GNNs by Learning Effective Selection Policies Beatrice Bevilacqua, Moshe Eliasof, Eli Meirom, Bruno Ribeiro, Haggai Maron

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

NeurIPS 2024 GRANOLA: Adaptive Normalization for Graph Neural Networks Moshe Eliasof, Beatrice Bevilacqua, Carola-Bibiane Schönlieb, Haggai Maron

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

NeurIPSW 2024 Random Propagations in GNNs Thu Bui, Anugunj Naman, Carola-Bibiane Schönlieb, Bruno Ribeiro, Beatrice Bevilacqua, Moshe Eliasof

NeurIPSW 2024 Rethinking Fine-Tuning Through Geometric Perspective Krishna Sri Ipsit Mantri, Moshe Eliasof, Carola-Bibiane Schönlieb, Bruno Ribeiro

NeurIPSW 2024 Towards Foundation Models on Graphs: An Analysis on Cross-Dataset Transfer of Pretrained GNNs Fabrizio Frasca, Fabian Jogl, Moshe Eliasof, Matan Ostrovsky, Carola-Bibiane Schönlieb, Thomas Gärtner, Haggai Maron

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

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

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