no code implementations • 12 Dec 2021 • Volodymyr Kuleshov, Evgenii Nikishin, Shantanu Thakoor, Tingfung Lau, Stefano Ermon
In this work, we seek to understand and extend adversarial examples across domains in which inputs are discrete, particularly across new domains, such as computational biology.
no code implementations • 21 Nov 2021 • Tingfung Lau, Sailun Xu, Xinze Wang
These deep generative models provide away to utilize all the unlabeled images and videos online, since it can learn deep feature representations with unsupervised manner.
no code implementations • 9 Apr 2019 • Tingfung Lau, Nathan Ng, Julian Gingold, Nina Desai, Julian McAuley, Zachary C. Lipton
First, noting that in each image the embryo occupies a small subregion, we jointly train a region proposal network with the downstream classifier to isolate the embryo.
6 code implementations • 13 Feb 2019 • Shengyu Zhao, Tingfung Lau, Ji Luo, Eric I-Chao Chang, Yan Xu
3D medical image registration is of great clinical importance.
no code implementations • ICLR 2018 • Volodymyr Kuleshov, Shantanu Thakoor, Tingfung Lau, Stefano Ermon
Modern machine learning algorithms are often susceptible to adversarial examples — maliciously crafted inputs that are undetectable by humans but that fool the algorithm into producing undesirable behavior.