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 ...
Publications
Explore 912 academic publications
Showing 12 of
912 publications
Inference of Population Structure Using Multilocus Genotype Data: Linked Loci and Correlated Allele Frequencies
Abstract We describe extensions to the method of Pritchard et al. for inferring population structure from multilocus genotype data. Most importantly, we develop methods that all...
Organizational Learning: The Contributing Processes and the Literatures
This paper differs from previous examinations of organizational learning in that it is broader in scope and more evaluative of the literatures. Four constructs related to organi...
Recombinant genomes which express chloramphenicol acetyltransferase in mammalian cells.
We constructed a series of recombinant genomes which directed expression of the enzyme chloramphenicol acetyltransferase (CAT) in mammalian cells. The prototype recombinant in t...
Cancer statistics, 2024
Abstract Each year, the American Cancer Society estimates the numbers of new cancer cases and deaths in the United States and compiles the most recent data on population‐based c...
The spread of true and false news online
Lies spread faster than the truth There is worldwide concern over false news and the possibility that it can influence political, economic, and social well-being. To understand ...
Genome sequencing in microfabricated high-density picolitre reactors
The proliferation of large-scale DNA-sequencing projects in recent years has driven a search for alternative methods to reduce time and cost. Here we describe a scalable, highly...
Remdesivir for the Treatment of Covid-19 — Final Report
Our data show that remdesivir was superior to placebo in shortening the time to recovery in adults who were hospitalized with Covid-19 and had evidence of lower respiratory trac...
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...