Jue Wang

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Publications associées (4)

Fast Adversarial Training With Adaptive Step Size

Mathieu Salzmann, Sabine Süsstrunk, Jue Wang, Chen Liu, Yong Zhang, Zhuoyi Huang

While adversarial training and its variants have shown to be the most effective algorithms to defend against adversarial attacks, their extremely slow training process makes it hard to scale to large datasets like ImageNet. The key idea of recent works to ...

Ieee-Inst Electrical Electronics Engineers Inc2023

Track: Machine Learning in Protein Science De Novo Design of Viral Epitope Mimetics with Non-Regular Structural Features

Jue Wang, Bruno Emanuel Ferreira De Sousa Correia, Karla Montserrat Castro Gilabert, Anastassia Andreevna Vorobieva

WILEY2023

Scaffolding protein functional sites using deep learning

Basile Isidore Martin Wicky, Jue Wang, Bruno Emanuel Ferreira De Sousa Correia, Karla Montserrat Castro Gilabert, Wayne Yang Wen Wei

The binding and catalytic functions of proteins are generally mediated by a small number of functional residues held in place by the overall protein structure. Here, we describe deep learning approaches for scaffolding such functional sites without needing ...

American Association for the Advancement of Science2022

The Sixth Visual Object Tracking VOT2018 Challenge Results

Jiri Matas, Li Wang, Qing Guo, Jue Wang, Wei Wu, Yunpeng Li, Xiaofan Zhang, Qiang Wang, Erhan Gündogdu, Wenjun Zeng, Bo Chen, Luca Bertinetto, Siwen Wang, Hongwei Li, Chong Sun, Tianzong Zhang, Yuxuan Sun, Peixia Li, Yunhua Zhang, Ran Tao, Namhoon Lee, Zhiye Wang, Bo Li, Litu Rout, Zeyu Zhang, Tianyang Xu, Yi Wu, Feng Li, Ning Wang, Jing Li

The Visual Object Tracking challenge VOT2018 is the sixth annual tracker benchmarking activity organized by the VOT initiative. Results of over eighty trackers are presented; many are state-of-the-art trackers published at major computer vision conferences ...

SPRINGER INTERNATIONAL PUBLISHING AG2019

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