Purpose: Because of the dismal outcomes of conventional therapies for pancreatic
carcinomas, we postulated that hypoxia may exist within these tumors. Methods and�…

Convolutional layers are one of the basic building blocks of modern deep neural networks.
One fundamental assumption is that convolutional kernels should be shared for all�…

Purpose: Persistently elevated posttreatment plasma EBV DNA is a robust predictor of
relapse in nasopharyngeal carcinoma (NPC). However, assay standardization is necessary�…

Adversarial examples are commonly viewed as a threat to ConvNets. Here we present an
opposite perspective: adversarial examples can be used to improve image recognition�…

Much research on object detection focuses on building better model architectures and
detection algorithms. Changing the model architecture, however, comes at the cost of�…

Pre-training is a dominant paradigm in computer vision. For example, supervised ImageNet
pre-training is commonly used to initialize the backbones of object detection and�…

We introduce the antibody landscape, a method for the quantitative analysis of antibody-
mediated immunity to antigenically variable pathogens, achieved by accounting for�…

As a fundamental problem in pattern recognition, graph matching has applications in a
variety of fields, from computer vision to computational biology. In graph matching, patterns�…

Neural Machine Translation (NMT) has shown remarkable progress over the past few years
with production systems now being deployed to end-users. One major drawback of current�…

We revisit the design choices in Transformers, and propose methods to address their
weaknesses in handling long sequences. First, we propose a simple layer named gated�…