| PDE-GCN: Novel architectures for graph neural networks motivated by partial differential equations M Eliasof, E Haber, E Treister Advances in Neural Information Processing Systems 34, 2021 | 119 | 2021 |
| pathGCN: Learning General Graph Spatial Operators from Paths M Eliasof, E Haber, E Treister International Conference on Machine Learning, 5878-5891, 2022 | 25 | 2022 |
| DiffGCN: Graph Convolutional Networks via Differential Operators and Algebraic Multigrid Pooling M Eliasof, E Treister Thirty-fourth Conference on Neural Information Processing Systems (NeurIPS) 2020, 2020 | 23 | 2020 |
| Leanconvnets: Low-cost yet effective convolutional neural networks J Ephrath, M Eliasof, L Ruthotto, E Haber, E Treister IEEE Journal of Selected Topics in Signal Processing 14 (4), 894-904, 2020 | 21* | 2020 |
| Mimetic neural networks: A unified framework for protein design and folding M Eliasof, T Boesen, E Haber, C Keasar, E Treister Frontiers in Bioinformatics 2, 39, 2022 | 12 | 2022 |
| Improving Graph Neural Networks with Learnable Propagation Operators M Eliasof, L Ruthotto, E Treister 40th International Conference on Machine Learning (ICML), 2023 | 11 | 2023 |
| Mgic: Multigrid-in-channels neural network architectures M Eliasof, J Ephrath, L Ruthotto, E Treister SIAM Journal on Scientific Computing 45 (3), S307-S328, 2023 | 9* | 2023 |
| Feature Transportation Improves Graph Neural Networks M Eliasof, E Haber, E Treister Proceedings of the AAAI Conference on Artificial Intelligence 38 (11), 11874 …, 2024 | 8* | 2024 |
| Multimodal 3D Shape Reconstruction under Calibration Uncertainty Using Parametric Level Set Methods M Eliasof, A Sharf, E Treister SIAM Journal on Imaging Sciences 13 (1), 265-290, 2020 | 8 | 2020 |
| Rethinking Unsupervised Neural Superpixel Segmentation M Eliasof, NB Zikri, E Treister 2022 IEEE International Conference on Image Processing (ICIP), 3500-3504, 2022 | 7 | 2022 |
| Efficient Subgraph GNNs by Learning Effective Selection Policies B Bevilacqua, M Eliasof, E Meirom, B Ribeiro, H Maron ICLR 2024, 2024 | 6 | 2024 |
| Haar wavelet feature compression for quantized graph convolutional networks M Eliasof, BJ Bodner, E Treister IEEE Transactions on Neural Networks and Learning Systems, 2023 | 6 | 2023 |
| Haar Wavelet Feature Compression for Quantized Graph Convolutional Networks M Eliasof, BJ Bodner, E Treister IEEE Transactions on Neural Networks and Learning Systems, 2023 | 6 | 2023 |
| Quantized convolutional neural networks through the lens of partial differential equations I Ben-Yair, G Ben Shalom, M Eliasof, E Treister Research in the Mathematical Sciences 9 (4), 58, 2022 | 5 | 2022 |
| DRIP: Deep Regularizers for Inverse Problems M Eliasof, E Haber, E Treister Inverse Problems 40, 2024 | 4 | 2024 |
| Graph Positional Encoding via Random Feature Propagation M Eliasof, F Frasca, B Bevilacqua, E Treister, G Chechik, H Maron 40th International Conference on Machine Learning (ICML), 2023 | 3 | 2023 |
| Estimating a potential without the agony of the partition function E Haber, M Eliasof, L Tenorio SIAM Journal on Mathematics of Data Science 5 (4), 1005-1027, 2023 | 2 | 2023 |
| Estimating a potential without the agony of the partition function E Haber, M Eliasof, L Tenorio SIAM Journal on Mathematics of Data Science 5 (4), 1005-1027, 2023 | 2 | 2023 |
| GRANOLA: Adaptive Normalization for Graph Neural Networks M Eliasof, B Bevilacqua, CB Schönlieb, H Maron arXiv preprint arXiv:2404.13344, 2024 | 1 | 2024 |
| An Over Complete Deep Learning Method for Inverse Problems M Eliasof, E Haber, E Treister arXiv preprint arXiv:2402.04653, 2024 | 1 | 2024 |
Eran TreisterComputer Science Dept at Ben-Gurion University在 cs.bgu.ac.il 的电子邮件经过验证
