145 citations · 205 across the 12 of their papers we have counts for
5 papers · 1 filter
De Novo Molecular Generation with Stacked Adversarial Model
Yuansan Liu, James Bailey
Generating novel drug molecules with desired biological properties is a time consuming and complex task. Conditional generative adversarial models have recently been proposed as pr…
Alpha-IoU: A Family of Power Intersection over Union Losses for Bounding Box Regression
Jiabo He, Sarah Erfani, Xingjun Ma +3
Bounding box (bbox) regression is a fundamental task in computer vision. So far, the most commonly used loss functions for bbox regression are the Intersection over Union (IoU) los…
Exploring Architectural Ingredients of Adversarially Robust Deep Neural Networks
Hanxun Huang, Yisen Wang, Sarah Monazam Erfani +3
Deep neural networks (DNNs) are known to be vulnerable to adversarial attacks. A range of defense methods have been proposed to train adversarially robust DNNs, among which adversa…
Semantic-Preserving Adversarial Text Attacks
Xinghao Yang, Weifeng Liu, James Bailey +2
Deep neural networks (DNNs) are known to be vulnerable to adversarial images, while their robustness in text classification is rarely studied. Several lines of text attack methods…
What Do Deep Nets Learn? Class-wise Patterns Revealed in the Input Space
Shihao Zhao, Xingjun Ma, Yisen Wang +3
Deep neural networks (DNNs) are increasingly deployed in different applications to achieve state-of-the-art performance. However, they are often applied as a black box with limited…