Moshe Eliasof - RankMe

92 papers A* 17A 4B 1Journal 69Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	A*	`conf`	Graph Flow Matching: Enhancing Image Generation with Neighbor-Aware Flow Fields. AAAI Md Shahriar Rahim Siddiqui, Moshe Eliasof, Eldad Haber
2026	J	`jnl`	Learning from Historical Activations in Graph Neural Networks. CoRR Yaniv Galron, Hadar Sinai, Haggai Maron, Moshe Eliasof
2026	J	`jnl`	Multiscale Training of Convolutional Neural Networks. Trans. Mach. Learn. Res. Shadab Ahamed, Niloufar Zakariaei, Eldad Haber, Moshe Eliasof
2026	J	`jnl`	PDE-SSM: A Spectral State Space Approach to Spatial Mixing in Diffusion Transformers. CoRR Eshed Gal, Moshe Eliasof, Siddharth Rout, Eldad Haber
2026	J	`jnl`	Preconditioned Score and Flow Matching. CoRR Shadab Ahamed, Eshed Gal, Simon Ghyselincks, Md Shahriar Rahim Siddiqui, Moshe Eliasof, Eldad Haber
2026	J	`jnl`	Towards Improved Sentence Representations using Token Graphs. CoRR Krishna Sri Ipsit Mantri, Carola-Bibiane Schönlieb, Zorah Lähner, Moshe Eliasof
2026	J	`jnl`	Trajectory Stitching for Solving Inverse Problems with Flow-Based Models. CoRR Alexander Denker, Moshe Eliasof, Zeljko Kereta, Carola-Bibiane Schönlieb
2025	A*	`conf`	DiTASK: Multi-Task Fine-Tuning with Diffeomorphic Transformations. CVPR Krishna Sri Ipsit Mantri, Carola-Bibiane Schönlieb, Bruno Ribeiro, Chaim Baskin, Moshe Eliasof
2025	J	`jnl`	DiTASK: Multi-Task Fine-Tuning with Diffeomorphic Transformations. CoRR Krishna Sri Ipsit Mantri, Carola-Bibiane Schönlieb, Bruno Ribeiro, Chaim Baskin, Moshe Eliasof
2025	A*	`conf`	Estimation of single-cell and tissue perturbation effect in spatial transcriptomics via Spatial Causal Disentanglement. ICLR Stathis Megas, Daniel G. Chen, Krzysztof Polanski, Moshe Eliasof, Carola-Bibiane Schönlieb, Sarah A. Teichmann
2025	J	`jnl`	FLASH: Flexible Learning of Adaptive Sampling from History in Temporal Graph Neural Networks. CoRR Or Feldman, Krishna Sri Ipsit Mantri, Carola-Bibiane Schönlieb, Chaim Baskin, Moshe Eliasof
2025	J	`jnl`	GRAMA: Adaptive Graph Autoregressive Moving Average Models. CoRR Moshe Eliasof, Alessio Gravina, Andrea Ceni, Claudio Gallicchio, Davide Bacciu, Carola-Bibiane Schönlieb
2025	A*	`conf`	Graph Adaptive Autoregressive Moving Average Models. ICML Moshe Eliasof, Alessio Gravina, Andrea Ceni, Claudio Gallicchio, Davide Bacciu, Carola-Bibiane Schönlieb
2025	J	`jnl`	Graph Flow Matching: Enhancing Image Generation with Neighbor-Aware Flow Fields. CoRR Md Shahriar Rahim Siddiqui, Moshe Eliasof, Eldad Haber
2025	J	`jnl`	Graph Neural Regularizers for PDE Inverse Problems. CoRR William Lauga, James Rowbottom, Alexander Denker, Zeljko Kereta, Moshe Eliasof, Carola-Bibiane Schönlieb
2025	A*	`conf`	Improving the Effective Receptive Field of Message-Passing Neural Networks. ICML Shahaf E. Finder, Ron Shapira Weber, Moshe Eliasof, Oren Freifeld, Eran Treister
2025	J	`jnl`	Improving the Effective Receptive Field of Message-Passing Neural Networks. CoRR Shahaf E. Finder, Ron Shapira Weber, Moshe Eliasof, Oren Freifeld, Eran Treister
2025	J	`jnl`	Iterative Flow Matching - Path Correction and Gradual Refinement for Enhanced Generative Modeling. CoRR Eldad Haber, Shadab Ahamed, Md Shahriar Rahim Siddiqui, Niloufar Zakariaei, Moshe Eliasof
2025	A*	`conf`	Learning Regularization for Graph Inverse Problems. AAAI Moshe Eliasof, Md Shahriar Rahim Siddiqui, Carola-Bibiane Schönlieb, Eldad Haber
2025	J	`jnl`	Message-Passing State-Space Models: Improving Graph Learning with Modern Sequence Modeling. CoRR Andrea Ceni, Alessio Gravina, Claudio Gallicchio, Davide Bacciu, Carola-Bibiane Schönlieb, Moshe Eliasof
2025	J	`jnl`	Multiscale Training of Convolutional Neural Networks. CoRR Niloufar Zakariaei, Shadab Ahamed, Eldad Haber, Moshe Eliasof
2025	A*	`conf`	On Oversquashing in Graph Neural Networks Through the Lens of Dynamical Systems. AAAI Alessio Gravina, Moshe Eliasof, Claudio Gallicchio, Davide Bacciu, Carola-Bibiane Schönlieb
2025	J	`jnl`	On The Expressive Power of GNN Derivatives. CoRR Yam Eitan, Moshe Eliasof, Yoav Gelberg, Fabrizio Frasca, Guy Bar-Shalom, Haggai Maron
2025	J	`jnl`	On the Effectiveness of Random Weights in Graph Neural Networks. CoRR Thu Bui, Carola-Bibiane Schönlieb, Bruno Ribeiro, Beatrice Bevilacqua, Moshe Eliasof
2025	J	`jnl`	One-Step Offline Distillation of Diffusion-based Models via Koopman Modeling. CoRR Nimrod Berman, Ilan Naiman, Moshe Eliasof, Hedi Zisling, Omri Azencot
2025	A	`conf`	Quadratic Binary Optimization with Graph Neural Networks. ECAI Moshe Eliasof, Eldad Haber
2025	J	`jnl`	Return of ChebNet: Understanding and Improving an Overlooked GNN on Long Range Tasks. CoRR Ali Hariri, Alvaro Arroyo, Alessio Gravina, Moshe Eliasof, Carola-Bibiane Schönlieb, Davide Bacciu, Kamyar Azizzadenesheli, Xiaowen Dong, Pierre Vandergheynst
2025	J	`jnl`	Reversing Large Language Models for Efficient Training and Fine-Tuning. CoRR Eshed Gal, Moshe Eliasof, Javier Turek, Uri M. Ascher, Eran Treister, Eldad Haber
2025	J	`jnl`	Revisiting Node Affinity Prediction in Temporal Graphs. CoRR Krishna Sri Ipsit Mantri, Or Feldman, Moshe Eliasof, Chaim Baskin
2025	J	`jnl`	TANGO: Graph Neural Dynamics via Learned Energy and Tangential Flows. CoRR Moshe Eliasof, Eldad Haber, Carola-Bibiane Schönlieb
2025	J	`jnl`	Towards Efficient Training of Graph Neural Networks: A Multiscale Approach. CoRR Eshed Gal, Moshe Eliasof, Carola-Bibiane Schönlieb, Eldad Haber, Eran Treister
2025	J	`jnl`	Towards Efficient Training of Graph Neural Networks: A Multiscale Approach. Trans. Mach. Learn. Res. Eshed Gal, Moshe Eliasof, Carola-Bibiane Schönlieb, Ivan I. Kyrchei, Eldad Haber, Eran Treister
2025	J	`jnl`	Towards Graph Foundation Models: A Study on the Generalization of Positional and Structural Encodings. Trans. Mach. Learn. Res. Billy Joe Franks, Moshe Eliasof, Semih Cantürk, Guy Wolf, Carola-Bibiane Schönlieb, Sophie Fellenz, Marius Kloft
2025	J	`jnl`	Towards Invariance to Node Identifiers in Graph Neural Networks. CoRR Maya Bechler-Speicher, Moshe Eliasof, Carola-Bibiane Schönlieb, Ran Gilad-Bachrach, Amir Globerson
2025	J	`jnl`	Understanding and Improving Laplacian Positional Encodings For Temporal GNNs. CoRR Yaniv Galron, Fabrizio Frasca, Haggai Maron, Eran Treister, Moshe Eliasof
2025	—	`conf`	Understanding and Improving Laplacian Positional Encodings for Temporal GNNs. ECML/PKDD (2) Yaniv Galron, Fabrizio Frasca, Haggai Maron, Eran Treister, Moshe Eliasof
2024	J	`jnl`	A General Recipe for Contractive Graph Neural Networks - Technical Report. CoRR Maya Bechler-Speicher, Moshe Eliasof
2024	A*	`conf`	Advection Augmented Convolutional Neural Networks. NeurIPS Niloufar Zakariaei, Siddharth Rout, Eldad Haber, Moshe Eliasof
2024	J	`jnl`	Advection Augmented Convolutional Neural Networks. CoRR Niloufar Zakariaei, Siddharth Rout, Eldad Haber, Moshe Eliasof
2024	J	`jnl`	An Over Complete Deep Learning Method for Inverse Problems. CoRR Moshe Eliasof, Eldad Haber, Eran Treister
2024	J	`jnl`	Celcomen: spatial causal disentanglement for single-cell and tissue perturbation modeling. CoRR Stathis Megas, Daniel G. Chen, Krzysztof Polanski, Moshe Eliasof, Carola-Bibiane Schönlieb, Sarah A. Teichmann
2024	A*	`conf`	DiGRAF: Diffeomorphic Graph-Adaptive Activation Function. NeurIPS Krishna Sri Ipsit Mantri, Xinzhi Wang, Carola-Bibiane Schönlieb, Bruno Ribeiro, Beatrice Bevilacqua, Moshe Eliasof
2024	J	`jnl`	DiGRAF: Diffeomorphic Graph-Adaptive Activation Function. CoRR Krishna Sri Ipsit Mantri, Xinzhi Wang, Carola-Bibiane Schönlieb, Bruno Ribeiro, Beatrice Bevilacqua, Moshe Eliasof
2024	A*	`conf`	Efficient Subgraph GNNs by Learning Effective Selection Policies. ICLR Beatrice Bevilacqua, Moshe Eliasof, Eli A. Meirom, Bruno Ribeiro, Haggai Maron
2024	A	`conf`	Every Node Counts: Improving the Training of Graph Neural Networks on Node Classification. ECAI Moshe Eliasof, Eldad Haber, Eran Treister
2024	A*	`conf`	Feature Transportation Improves Graph Neural Networks. AAAI Moshe Eliasof, Eldad Haber, Eran Treister
2024	A*	`conf`	GRANOLA: Adaptive Normalization for Graph Neural Networks. NeurIPS Moshe Eliasof, Beatrice Bevilacqua, Carola-Bibiane Schönlieb, Haggai Maron
2024	J	`jnl`	GRANOLA: Adaptive Normalization for Graph Neural Networks. CoRR Moshe Eliasof, Beatrice Bevilacqua, Carola-Bibiane Schönlieb, Haggai Maron
2024	J	`jnl`	Global-Local Graph Neural Networks for Node-Classification. CoRR Moshe Eliasof, Eran Treister
2024	J	`jnl`	Global-local graph neural networks for node-classification. Pattern Recognit. Lett. Moshe Eliasof, Eran Treister
2024	J	`jnl`	Graph Neural Networks for Binary Programming. CoRR Moshe Eliasof, Eldad Haber
2024	J	`jnl`	Graph Neural Reaction Diffusion Models. CoRR Moshe Eliasof, Eldad Haber, Eran Treister
2024	J	`jnl`	Graph Neural Reaction Diffusion Models. SIAM J. Sci. Comput. Moshe Eliasof, Eldad Haber, Eran Treister
2024	J	`jnl`	Haar Wavelet Feature Compression for Quantized Graph Convolutional Networks. IEEE Trans. Neural Networks Learn. Syst. Moshe Eliasof, Benjamin Jacob Bodner, Eran Treister
2024	J	`jnl`	Learning Regularization for Graph Inverse Problems. CoRR Moshe Eliasof, Md Shahriar Rahim Siddiqui, Carola-Bibiane Schönlieb, Eldad Haber
2024	A	`conf`	On The Temporal Domain of Differential Equation Inspired Graph Neural Networks. AISTATS Moshe Eliasof, Eldad Haber, Eran Treister, Carola-Bibiane Schönlieb
2024	J	`jnl`	On The Temporal Domain of Differential Equation Inspired Graph Neural Networks. CoRR Moshe Eliasof, Eldad Haber, Eran Treister, Carola-Bibiane Schönlieb
2024	J	`jnl`	On the Utilization of Unique Node Identifiers in Graph Neural Networks. CoRR Maya Bechler-Speicher, Moshe Eliasof, Carola-Bibiane Schönlieb, Ran Gilad-Bachrach, Amir Globerson
2024	A	`conf`	Resilient Graph Neural Networks: A Coupled Dynamical Systems Approach. ECAI Moshe Eliasof, Davide Murari, Ferdia Sherry, Carola-Bibiane Schönlieb
2024	J	`jnl`	Tackling Graph Oversquashing by Global and Local Non-Dissipativity. CoRR Alessio Gravina, Moshe Eliasof, Claudio Gallicchio, Davide Bacciu, Carola-Bibiane Schönlieb
2024	J	`jnl`	Towards Foundation Models on Graphs: An Analysis on Cross-Dataset Transfer of Pretrained GNNs. CoRR Fabrizio Frasca, Fabian Jogl, Moshe Eliasof, Matan Ostrovsky, Carola-Bibiane Schönlieb, Thomas Gärtner, Haggai Maron
2024	J	`jnl`	Towards Graph Foundation Models: A Study on the Generalization of Positional and Structural Encodings. CoRR Billy Joe Franks, Moshe Eliasof, Semih Cantürk, Guy Wolf, Carola-Bibiane Schönlieb, Sophie Fellenz, Marius Kloft
2023	J	`jnl`	ADR-GNN: Advection-Diffusion-Reaction Graph Neural Networks. CoRR Moshe Eliasof, Eldad Haber, Eran Treister
2023	J	`jnl`	Contractive Systems Improve Graph Neural Networks Against Adversarial Attacks. CoRR Moshe Eliasof, Davide Murari, Ferdia Sherry, Carola-Bibiane Schönlieb
2023	J	`jnl`	DRIP: Deep Regularizers for Inverse Problems. CoRR Moshe Eliasof, Eldad Haber, Eran Treister
2023	J	`jnl`	Efficient Subgraph GNNs by Learning Effective Selection Policies. CoRR Beatrice Bevilacqua, Moshe Eliasof, Eli A. Meirom, Bruno Ribeiro, Haggai Maron
2023	J	`jnl`	Estimating a Potential Without the Agony of the Partition Function. SIAM J. Math. Data Sci. Eldad Haber, Moshe Eliasof, Luis Tenorio
2023	A*	`conf`	Graph Positional Encoding via Random Feature Propagation. ICML Moshe Eliasof, Fabrizio Frasca, Beatrice Bevilacqua, Eran Treister, Gal Chechik, Haggai Maron
2023	J	`jnl`	Graph Positional Encoding via Random Feature Propagation. CoRR Moshe Eliasof, Fabrizio Frasca, Beatrice Bevilacqua, Eran Treister, Gal Chechik, Haggai Maron
2023	A*	`conf`	Improving Graph Neural Networks with Learnable Propagation Operators. ICML Moshe Eliasof, Lars Ruthotto, Eran Treister
2023	J	`jnl`	MGIC: Multigrid-in-Channels Neural Network Architectures. SIAM J. Sci. Comput. Moshe Eliasof, Jonathan Ephrath, Lars Ruthotto, Eran Treister
2022	J	`jnl`	Estimating a potential without the agony of the partition function. CoRR Eldad Haber, Moshe Eliasof, Luis Tenorio
2022	J	`jnl`	Every Node Counts: Improving the Training of Graph Neural Networks on Node Classification. CoRR Moshe Eliasof, Eldad Haber, Eran Treister
2022	J	`jnl`	Mimetic Neural Networks: A Unified Framework for Protein Design and Folding. Frontiers Bioinform. Moshe Eliasof, Tue Boesen, Eldad Haber, Chen Keasar, Eran Treister
2022	B	`conf`	Rethinking Unsupervised Neural Superpixel Segmentation. ICIP Moshe Eliasof, Nir Ben Zikri, Eran Treister
2022	J	`jnl`	Rethinking Unsupervised Neural Superpixel Segmentation. CoRR Moshe Eliasof, Nir Ben Zikri, Eran Treister
2022	J	`jnl`	Unsupervised Image Semantic Segmentation through Superpixels and Graph Neural Networks. CoRR Moshe Eliasof, Nir Ben Zikri, Eran Treister
2022	A*	`conf`	pathGCN: Learning General Graph Spatial Operators from Paths. ICML Moshe Eliasof, Eldad Haber, Eran Treister
2022	J	`jnl`	pathGCN: Learning General Graph Spatial Operators from Paths. CoRR Moshe Eliasof, Eldad Haber, Eran Treister
2022	J	`jnl`	ωGNNs: Deep Graph Neural Networks Enhanced by Multiple Propagation Operators. CoRR Moshe Eliasof, Lars Ruthotto, Eran Treister
2021	J	`jnl`	Haar Wavelet Feature Compression for Quantized Graph Convolutional Networks. CoRR Moshe Eliasof, Benjamin Bodner, Eran Treister
2021	J	`jnl`	Mimetic Neural Networks: A unified framework for Protein Design and Folding. CoRR Moshe Eliasof, Tue Boesen, Eldad Haber, Chen Keasar, Eran Treister
2021	A*	`conf`	PDE-GCN: Novel Architectures for Graph Neural Networks Motivated by Partial Differential Equations. NeurIPS Moshe Eliasof, Eldad Haber, Eran Treister
2021	J	`jnl`	PDE-GCN: Novel Architectures for Graph Neural Networks Motivated by Partial Differential Equations. CoRR Moshe Eliasof, Eldad Haber, Eran Treister
2021	J	`jnl`	Quantized convolutional neural networks through the lens of partial differential equations. CoRR Ido Ben-Yair, Gil Ben Shalom, Moshe Eliasof, Eran Treister
2020	A*	`conf`	DiffGCN: Graph Convolutional Networks via Differential Operators and Algebraic Multigrid Pooling. NeurIPS Moshe Eliasof, Eran Treister
2020	J	`jnl`	DiffGCN: Graph Convolutional Networks via Differential Operators and Algebraic Multigrid Pooling. CoRR Moshe Eliasof, Eran Treister
2020	J	`jnl`	LeanConvNets: Low-Cost Yet Effective Convolutional Neural Networks. IEEE J. Sel. Top. Signal Process. Jonathan Ephrath, Moshe Eliasof, Lars Ruthotto, Eldad Haber, Eran Treister
2020	J	`jnl`	Multigrid-in-Channels Neural Network Architectures. CoRR Moshe Eliasof, Jonathan Ephrath, Lars Ruthotto, Eran Treister
2020	J	`jnl`	Multimodal 3D Shape Reconstruction under Calibration Uncertainty Using Parametric Level Set Methods. SIAM J. Imaging Sci. Moshe Eliasof, Andrei Sharf, Eran Treister
2019	J	`jnl`	LeanConvNets: Low-cost Yet Effective Convolutional Neural Networks. CoRR Jonathan Ephrath, Moshe Eliasof, Lars Ruthotto, Eldad Haber, Eran Treister
2019	J	`jnl`	Multi-modal 3D Shape Reconstruction Under Calibration Uncertainty using Parametric Level Set Methods. CoRR Moshe Eliasof, Andrei Sharf, Eran Treister