5 citations · 6 across the 2 of their papers we have counts for
6 papers
On the Spectral Bias of Convolutional Neural Tangent and Gaussian Process Kernels
Amnon Geifman, Meirav Galun, David Jacobs +1
We study the properties of various over-parametrized convolutional neural architectures through their respective Gaussian process and neural tangent kernels. We prove that, with no…
Spectral Analysis of the Neural Tangent Kernel for Deep Residual Networks
Yuval Belfer, Amnon Geifman, Meirav Galun +1
Deep residual network architectures have been shown to achieve superior accuracy over classical feed-forward networks, yet their success is still not fully understood. Focusing on…
On the Similarity between the Laplace and Neural Tangent Kernels
Amnon Geifman, Abhay Yadav, Yoni Kasten +3
Recent theoretical work has shown that massively overparameterized neural networks are equivalent to kernel regressors that use Neural Tangent Kernels(NTK). Experiments show that t…
Frequency Bias in Neural Networks for Input of Non-Uniform Density
Ronen Basri, Meirav Galun, Amnon Geifman +3
Recent works have partly attributed the generalization ability of over-parameterized neural networks to frequency bias -- networks trained with gradient descent on data drawn from…
Averaging Essential and Fundamental Matrices in Collinear Camera Settings
Amnon Geifman, Yoni Kasten, Meirav Galun +1
Global methods to Structure from Motion have gained popularity in recent years. A significant drawback of global methods is their sensitivity to collinear camera settings. In this…
Algebraic Characterization of Essential Matrices and Their Averaging in Multiview Settings
Yoni Kasten, Amnon Geifman, Meirav Galun +1
Essential matrix averaging, i.e., the task of recovering camera locations and orientations in calibrated, multiview settings, is a first step in global approaches to Euclidean stru…