7 citations · 14 across the 4 of their papers we have counts for
4 papers
WINE: Wavelet-Guided GAN Inversion and Editing for High-Fidelity Refinement
Chaewon Kim, Seung-Jun Moon, Gyeong-Moon Park
Recent advanced GAN inversion models aim to convey high-fidelity information from original images to generators through methods using generator tuning or high-dimensional feature l…
Zero-shot Blind Image Denoising via Implicit Neural Representations
Chaewon Kim, Jaeho Lee, Jinwoo Shin
Recent denoising algorithms based on the "blind-spot" strategy show impressive blind image denoising performances, without utilizing any external dataset. While the methods excel i…
Scaling Neural Tangent Kernels via Sketching and Random Features
Amir Zandieh, Insu Han, Haim Avron +3
The Neural Tangent Kernel (NTK) characterizes the behavior of infinitely-wide neural networks trained under least squares loss by gradient descent. Recent works also report that NT…
Random Features for the Neural Tangent Kernel
Insu Han, Haim Avron, Neta Shoham +2
The Neural Tangent Kernel (NTK) has discovered connections between deep neural networks and kernel methods with insights of optimization and generalization. Motivated by this, rece…