71 citations · 153 across the 8 of their papers we have counts for
8 papers
Can one hear the shape of a neural network?: Snooping the GPU via Magnetic Side Channel
Henrique Teles Maia, Chang Xiao, Dingzeyu Li +2
Neural network applications have become popular in both enterprise and personal settings. Network solutions are tuned meticulously for each task, and designs that can robustly reso…
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,…
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…
Mechanics-Aware Modeling of Cloth Appearance
Zahra Montazeri, Chang Xiao, Yun +3
Micro-appearance models have brought unprecedented fidelity and details to cloth rendering. Yet, these models neglect fabric mechanics: when a piece of cloth interacts with the env…
Rethinking Generative Mode Coverage: A Pointwise Guaranteed Approach
Peilin Zhong, Yuchen Mo, Chang Xiao +2
Many generative models have to combat . The conventional wisdom to this end is by reducing through training a statistical distance (such as -divergence)…
BourGAN: Generative Networks with Metric Embeddings
Chang Xiao, Peilin Zhong, Changxi Zheng
This paper addresses the mode collapse for generative adversarial networks (GANs). We view modes as a geometric structure of data distribution in a metric space. Under this geometr…
FontCode: Embedding Information in Text Documents using Glyph Perturbation
Chang Xiao, Cheng Zhang, Changxi Zheng
We introduce FontCode, an information embedding technique for text documents. Provided a text document with specific fonts, our method embeds user-specified information in the text…