62 citations · 62 across the 3 of their papers we have counts for
11 papers
DeepCAD: A Deep Generative Network for Computer-Aided Design Models
Rundi Wu, Chang Xiao, Changxi Zheng
Deep generative models of 3D shapes have received a great deal of research interest. Yet, almost all of them generate discrete shape representations, such as voxels, point clouds,…
Linear Semantics in Generative Adversarial Networks
Jianjin Xu, Changxi Zheng
Generative Adversarial Networks (GANs) are able to generate high-quality images, but it remains difficult to explicitly specify the semantics of synthesized images. In this work, w…
Listening to Sounds of Silence for Speech Denoising
Ruilin Xu, Rundi Wu, Yuko Ishiwaka +2
We introduce a deep learning model for speech denoising, a long-standing challenge in audio analysis arising in numerous applications. Our approach is based on a key observation ab…
Differentiable Scattering Matrix for Optimization of Photonic Structures
Ziwei Zhu, Changxi Zheng
The scattering matrix, which quantifies the optical reflection and transmission of a photonic structure, is pivotal for understanding the performance of the structure. In many phot…
One Man's Trash is Another Man's Treasure: Resisting Adversarial Examples by Adversarial Examples
Chang Xiao, Changxi Zheng
Modern image classification systems are often built on deep neural networks, which suffer from adversarial examples--images with deliberately crafted, imperceptible noise to mislea…
Enhancing Adversarial Defense by k-Winners-Take-All
Chang Xiao, Peilin Zhong, Changxi Zheng
We propose a simple change to existing neural network structures for better defending against gradient-based adversarial attacks. Instead of using popular activation functions (suc…