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Moshe Eliasof
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2020 – today
- 2024
- [j8]Moshe Eliasof
, Eran Treister
Global-local graph neural networks for node-classification. Pattern Recognit. Lett. 184: 103-110 (2024) - [j7]Moshe Eliasof
Graph Neural Reaction Diffusion Models. SIAM J. Sci. Comput. 46(4): 399- (2024) - [j6]Moshe Eliasof, Benjamin Jacob Bodner
Haar Wavelet Feature Compression for Quantized Graph Convolutional Networks. IEEE Trans. Neural Networks Learn. Syst. 35(4): 4542-4553 (2024) - [c11]Moshe Eliasof, Eldad Haber, Eran Treister:
Feature Transportation Improves Graph Neural Networks. AAAI 2024: 11874-11882 - [c10]Moshe Eliasof, Eldad Haber, Eran Treister, Carola-Bibiane Schönlieb:
On The Temporal Domain of Differential Equation Inspired Graph Neural Networks. AISTATS 2024: 1792-1800 - [c9]Moshe Eliasof, Davide Murari, Ferdia Sherry, Carola-Bibiane Schönlieb:
Resilient Graph Neural Networks: A Coupled Dynamical Systems Approach. ECAI 2024: 1607-1614 - [c8]Moshe Eliasof, Eldad Haber, Eran Treister:
Every Node Counts: Improving the Training of Graph Neural Networks on Node Classification. ECAI 2024: 2508-2515 - [c7]Beatrice Bevilacqua, Moshe Eliasof, Eli A. Meirom, Bruno Ribeiro, Haggai Maron:
Efficient Subgraph GNNs by Learning Effective Selection Policies. ICLR 2024 - [i31]Moshe Eliasof, Eldad Haber, Eran Treister, Carola-Bibiane Schönlieb:
On The Temporal Domain of Differential Equation Inspired Graph Neural Networks. CoRR abs/2401.11074 (2024) - [i30]Moshe Eliasof, Eldad Haber, Eran Treister:
An Over Complete Deep Learning Method for Inverse Problems. CoRR abs/2402.04653 (2024) - [i29]Moshe Eliasof, Eldad Haber:
Graph Neural Networks for Binary Programming. CoRR abs/2404.04874 (2024) - [i28]Moshe Eliasof, Beatrice Bevilacqua, Carola-Bibiane Schönlieb, Haggai Maron:
GRANOLA: Adaptive Normalization for Graph Neural Networks. CoRR abs/2404.13344 (2024) - [i27]Alessio Gravina, Moshe Eliasof, Claudio Gallicchio, Davide Bacciu, Carola-Bibiane Schönlieb:
Tackling Graph Oversquashing by Global and Local Non-Dissipativity. CoRR abs/2405.01009 (2024) - [i26]Moshe Eliasof, Eran Treister:
Global-Local Graph Neural Networks for Node-Classification. CoRR abs/2406.10863 (2024) - [i25]Moshe Eliasof, Eldad Haber, Eran Treister:
Graph Neural Reaction Diffusion Models. CoRR abs/2406.10871 (2024) - [i24]Niloufar Zakariaei, Siddharth Rout, Eldad Haber, Moshe Eliasof:
Advection Augmented Convolutional Neural Networks. CoRR abs/2406.19253 (2024) - [i23]Krishna Sri Ipsit Mantri, Xinzhi Wang, Carola-Bibiane Schönlieb, Bruno Ribeiro, Beatrice Bevilacqua, Moshe Eliasof:
DiGRAF: Diffeomorphic Graph-Adaptive Activation Function. CoRR abs/2407.02013 (2024) - [i22]Moshe Eliasof, Md Shahriar Rahim Siddiqui, Carola-Bibiane Schönlieb, Eldad Haber:
Learning Regularization for Graph Inverse Problems. CoRR abs/2408.10436 (2024) - [i21]Stathis Megas, Daniel G. Chen, Krzysztof Polanski, Moshe Eliasof, Carola-Bibiane Schönlieb, Sarah A. Teichmann:
Celcomen: spatial causal disentanglement for single-cell and tissue perturbation modeling. CoRR abs/2409.05804 (2024) - [i20]Maya Bechler-Speicher, Moshe Eliasof:
A General Recipe for Contractive Graph Neural Networks - Technical Report. CoRR abs/2411.01717 (2024) - 2023
- [j5]Moshe Eliasof, Jonathan Ephrath, Lars Ruthotto
MGIC: Multigrid-in-Channels Neural Network Architectures. SIAM J. Sci. Comput. 45(3): S307-S328 (2023) - [j4]Eldad Haber, Moshe Eliasof, Luis Tenorio:
Estimating a Potential Without the Agony of the Partition Function. SIAM J. Math. Data Sci. 5(4): 1005-1027 (2023) - [c6]Moshe Eliasof, Fabrizio Frasca, Beatrice Bevilacqua, Eran Treister, Gal Chechik, Haggai Maron:
Graph Positional Encoding via Random Feature Propagation. ICML 2023: 9202-9223 - [c5]Moshe Eliasof, Lars Ruthotto
Improving Graph Neural Networks with Learnable Propagation Operators. ICML 2023: 9224-9245 - [i19]Moshe Eliasof, Fabrizio Frasca, Beatrice Bevilacqua, Eran Treister, Gal Chechik, Haggai Maron:
Graph Positional Encoding via Random Feature Propagation. CoRR abs/2303.02918 (2023) - [i18]Moshe Eliasof, Eldad Haber, Eran Treister:
DRIP: Deep Regularizers for Inverse Problems. CoRR abs/2304.00015 (2023) - [i17]Moshe Eliasof, Eldad Haber, Eran Treister:
ADR-GNN: Advection-Diffusion-Reaction Graph Neural Networks. CoRR abs/2307.16092 (2023) - [i16]Beatrice Bevilacqua, Moshe Eliasof, Eli A. Meirom, Bruno Ribeiro, Haggai Maron:
Efficient Subgraph GNNs by Learning Effective Selection Policies. CoRR abs/2310.20082 (2023) - [i15]Moshe Eliasof, Davide Murari, Ferdia Sherry
Contractive Systems Improve Graph Neural Networks Against Adversarial Attacks. CoRR abs/2311.06942 (2023) - 2022
- [j3]Moshe Eliasof, Tue Boesen, Eldad Haber, Chen Keasar, Eran Treister:
Mimetic Neural Networks: A Unified Framework for Protein Design and Folding. Frontiers Bioinform. 2 (2022) - [c4]Moshe Eliasof, Nir Ben Zikri, Eran Treister:
Rethinking Unsupervised Neural Superpixel Segmentation. ICIP 2022: 3500-3504 - [c3]Moshe Eliasof, Eldad Haber, Eran Treister:
pathGCN: Learning General Graph Spatial Operators from Paths. ICML 2022: 5878-5891 - [i14]Moshe Eliasof, Nir Ben Zikri, Eran Treister:
Rethinking Unsupervised Neural Superpixel Segmentation. CoRR abs/2206.10213 (2022) - [i13]Moshe Eliasof, Eldad Haber, Eran Treister:
pathGCN: Learning General Graph Spatial Operators from Paths. CoRR abs/2207.07408 (2022) - [i12]Eldad Haber, Moshe Eliasof, Luis Tenorio:
Estimating a potential without the agony of the partition function. CoRR abs/2208.09433 (2022) - [i11]Moshe Eliasof, Nir Ben Zikri, Eran Treister:
Unsupervised Image Semantic Segmentation through Superpixels and Graph Neural Networks. CoRR abs/2210.11810 (2022) - [i10]Moshe Eliasof, Lars Ruthotto, Eran Treister:
ωGNNs: Deep Graph Neural Networks Enhanced by Multiple Propagation Operators. CoRR abs/2210.17224 (2022) - [i9]Moshe Eliasof, Eldad Haber, Eran Treister:
Every Node Counts: Improving the Training of Graph Neural Networks on Node Classification. CoRR abs/2211.16631 (2022) - 2021
- [c2]Moshe Eliasof, Eldad Haber, Eran Treister:
PDE-GCN: Novel Architectures for Graph Neural Networks Motivated by Partial Differential Equations. NeurIPS 2021: 3836-3849 - [i8]Moshe Eliasof, Tue Boesen, Eldad Haber, Chen Keasar, Eran Treister:
Mimetic Neural Networks: A unified framework for Protein Design and Folding. CoRR abs/2102.03881 (2021) - [i7]Moshe Eliasof, Eldad Haber, Eran Treister:
PDE-GCN: Novel Architectures for Graph Neural Networks Motivated by Partial Differential Equations. CoRR abs/2108.01938 (2021) - [i6]Ido Ben-Yair, Gil Ben Shalom, Moshe Eliasof, Eran Treister:
Quantized convolutional neural networks through the lens of partial differential equations. CoRR abs/2109.00095 (2021) - [i5]Moshe Eliasof, Benjamin Bodner, Eran Treister:
Haar Wavelet Feature Compression for Quantized Graph Convolutional Networks. CoRR abs/2110.04824 (2021) - 2020
- [j2]Jonathan Ephrath, Moshe Eliasof, Lars Ruthotto
LeanConvNets: Low-Cost Yet Effective Convolutional Neural Networks. IEEE J. Sel. Top. Signal Process. 14(4): 894-904 (2020) - [j1]Moshe Eliasof, Andrei Sharf, Eran Treister
Multimodal 3D Shape Reconstruction under Calibration Uncertainty Using Parametric Level Set Methods. SIAM J. Imaging Sci. 13(1): 265-290 (2020) - [c1]Moshe Eliasof, Eran Treister:
DiffGCN: Graph Convolutional Networks via Differential Operators and Algebraic Multigrid Pooling. NeurIPS 2020 - [i4]Moshe Eliasof, Eran Treister
DiffGCN: Graph Convolutional Networks via Differential Operators and Algebraic Multigrid Pooling. CoRR abs/2006.04115 (2020) - [i3]Moshe Eliasof, Jonathan Ephrath, Lars Ruthotto, Eran Treister
Multigrid-in-Channels Neural Network Architectures. CoRR abs/2011.09128 (2020)
2010 – 2019
- 2019
- [i2]Moshe Eliasof, Andrei Sharf, Eran Treister:
Multi-modal 3D Shape Reconstruction Under Calibration Uncertainty using Parametric Level Set Methods. CoRR abs/1904.10379 (2019) - [i1]Jonathan Ephrath, Moshe Eliasof, Lars Ruthotto, Eldad Haber, Eran Treister:
LeanConvNets: Low-cost Yet Effective Convolutional Neural Networks. CoRR abs/1910.13157 (2019)
Coauthor Index
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