Publications

CBAM: Convolutional Block Attention Module

We propose Convolutional Block Attention Module (CBAM), a simple yet effective attention module for feed-forward convolutional neural networks. Given an intermediate feature map...

Generative Adversarial Nets

Racialized or ethnically marginalized groups typically have strong loyalties to particular political parties, but can these group loyalties be undermined? In this paper, I inves...

Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification

Rectified activation units (rectifiers) are essential for state-of-the-art neural networks. In this work, we study rectifier neural networks for image classification from two as...

Social network analysis methods and applications

Part I. Introduction: Networks, Relations, and Structure: 1. Relations and networks in the social and behavioral sciences 2. Social network data: collection and application Part...

New Algorithms and Methods to Estimate Maximum-Likelihood Phylogenies: Assessing the Performance of PhyML 3.0

PhyML is a phylogeny software based on the maximum-likelihood principle. Early PhyML versions used a fast algorithm performing nearest neighbor interchanges to improve a reasona...

STRING v11: protein–protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets

Proteins and their functional interactions form the backbone of the cellular machinery. Their connectivity network needs to be considered for the full understanding of biologica...

Wireless communications principles and practice

From the Publisher: The indispensable guide to wireless communications—now fully revised and updated! Wireless Communications: Principles and Practice, Second Edition is the...

How Many Interviews Are Enough?

Guidelines for determining nonprobabilistic sample sizes are virtually nonexistent. Purposive samples are the most commonly used form of nonprobabilistic sampling, and their siz...

A Simple, Positive Semi-Definite, Heteroskedasticity and Autocorrelation Consistent Covariance Matrix

This paper describes a simple method of calculating a heteroskedasticity and autocorrelation consistent covariance matrix that is positive semi-definite by construction. It also...

Cluster analysis and display of genome-wide expression patterns

A system of cluster analysis for genome-wide expression data from DNA microarray hybridization is described that uses standard statistical algorithms to arrange genes according ...

A Tutorial on Support Vector Machines for Pattern Recognition

A Fast Learning Algorithm for Deep Belief Nets

We show how to use “complementary priors” to eliminate the explaining-away effects that make inference difficult in densely connected belief nets that have many hidden layers. U...