| Frequency bias in neural networks for input of non-uniform density R Basri, M Galun, A Geifman, D Jacobs, Y Kasten, S Kritchman International conference on machine learning, 685-694, 2020 | 155 | 2020 |
| On the similarity between the laplace and neural tangent kernels A Geifman, A Yadav, Y Kasten, M Galun, D Jacobs, R Basri Advances in Neural Information Processing Systems, 2020 | 85 | 2020 |
| Algebraic characterization of essential matrices and their averaging in multiview settings Y Kasten, A Geifman, M Galun, R Basri Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 33 | 2019 |
| Gpsfm: Global projective sfm using algebraic constraints on multi-view fundamental matrices Y Kasten, A Geifman, M Galun, R Basri Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 26 | 2019 |
| Averaging essential and fundamental matrices in collinear camera settings A Geifman, Y Kasten, M Galun, R Basri Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 16 | 2020 |
| Spectral analysis of the neural tangent kernel for deep residual networks Y Belfer, A Geifman, M Galun, R Basri Journal of Machine Learning Research 25.184 (2024): 1-49., 2021 | 12 | 2021 |
| On the spectral bias of convolutional neural tangent and gaussian process kernels A Geifman, M Galun, D Jacobs, B Ronen Advances in Neural Information Processing Systems 35, 11253-11265, 2022 | 10 | 2022 |
| A kernel perspective of skip connections in convolutional networks D Barzilai, A Geifman, M Galun, R Basri arXiv preprint arXiv:2211.14810, 2022 | 9 | 2022 |
| Controlling the Inductive Bias of Wide Neural Networks by Modifying the Kernel's Spectrum A Geifman, D Barzilai, R Basri, M Galun arXiv preprint arXiv:2307.14531, 2023 | 2 | 2023 |
| On the Spectral Bias of Convolutional Neural Tangent and Gaussian Process Kernels – Supplementary Material – A Geifman, M Galun, D Jacobs, R Basri | | |
