15 citations · 50 across the 8 of their papers we have counts for
5 papers · 1 filter
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…
The Convergence Rate of Neural Networks for Learned Functions of Different Frequencies
Ronen Basri, David Jacobs, Yoni Kasten +1
We study the relationship between the frequency of a function and the speed at which a neural network learns it. We build on recent results that show that the dynamics of overparam…
Adversarially robust transfer learning
Ali Shafahi, Parsa Saadatpanah, Chen Zhu +4
Transfer learning, in which a network is trained on one task and re-purposed on another, is often used to produce neural network classifiers when data is scarce or full-scale train…
Understanding the (un)interpretability of natural image distributions using generative models
Ryen Krusinga, Sohil Shah, Matthias Zwicker +2
Probability density estimation is a classical and well studied problem, but standard density estimation methods have historically lacked the power to model complex and high-dimensi…