10 citations · 10 across the 3 of their papers we have counts for
3 papers
cs.LG2022
Identifying good directions to escape the NTK regime and efficiently learn low-degree plus sparse polynomials
Eshaan Nichani, Yu Bai, Jason D. Lee
A recent goal in the theory of deep learning is to identify how neural networks can escape the "lazy training," or Neural Tangent Kernel (NTK) regime, where the network is coupled…
cs.CV2021
Transforming the Latent Space of StyleGAN for Real Face Editing
Heyi Li, Jinlong Liu, Xinyu Zhang +3
Despite recent advances in semantic manipulation using StyleGAN, semantic editing of real faces remains challenging. The gap between the space and the + space demands an und…
cs.LG2020★ 10 cited
Understanding Why Neural Networks Generalize Well Through GSNR of Parameters
Jinlong Liu, Guoqing Jiang, Yunzhi Bai +2
As deep neural networks (DNNs) achieve tremendous success across many application domains, researchers tried to explore in many aspects on why they generalize well. In this paper,…