Publications

DeepWalk

We present DeepWalk, a novel approach for learning latent representations of\nvertices in a network. These latent representations encode social relations in\na continuous vector...

Factors Associated With Mental Health Outcomes Among Health Care Workers Exposed to Coronavirus Disease 2019

In this survey of heath care workers in hospitals equipped with fever clinics or wards for patients with COVID-19 in Wuhan and other regions in China, participants reported expe...

SCANPY: large-scale single-cell gene expression data analysis

Detection of 2019 novel coronavirus (2019-nCoV) by real-time RT-PCR

Background The ongoing outbreak of the recently emerged novel coronavirus (2019-nCoV) poses a challenge for public health laboratories as virus isolates are unavailable while th...

Multivariate Adaptive Regression Splines

A new method is presented for flexible regression modeling of high dimensional data. The model takes the form of an expansion in product spline basis functions, where the number...

The STRING database in 2021: customizable protein–protein networks, and functional characterization of user-uploaded gene/measurement sets

Abstract Cellular life depends on a complex web of functional associations between biomolecules. Among these associations, protein–protein interactions are particularly importan...

Path Aggregation Network for Instance Segmentation

The way that information propagates in neural networks is of great importance. In this paper, we propose Path Aggregation Network (PANet) aiming at boosting information flow in ...

UNet++: A Nested U-Net Architecture for Medical Image Segmentation

Social Capital: Prospects for a New Concept

A growing number of sociologists, political scientists, economists, and organizational theorists have invoked the concept of social capital in the search for answers to a broade...

A Comprehensive Survey on Graph Neural Networks

Deep learning has revolutionized many machine learning tasks in recent years, ranging from image classification and video processing to speech recognition and natural language u...

Laplacian Eigenmaps for Dimensionality Reduction and Data Representation

One of the central problems in machine learning and pattern recognition is to develop appropriate representations for complex data. We consider the problem of constructing a rep...

EfficientDet: Scalable and Efficient Object Detection

Model efficiency has become increasingly important in computer vision. In this paper, we systematically study neural network architecture design choices for object detection and...