Risk, Return, and Equilibrium: Empirical Tests
This paper tests the relationship between average return and risk for New York Stock Exchange common stocks. The theoretical basis of the tests is the "two-parameter" portfolio ...
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456 publications
Metascape provides a biologist-oriented resource for the analysis of systems-level datasets
A critical component in the interpretation of systems-level studies is the inference of enriched biological pathways and protein complexes contained within OMICs datasets. Succe...
Evaluating the Effectiveness of Large Language Models in Representing Textual Descriptions of Geometry and Spatial Relations (Short Paper)
This research focuses on assessing the ability of large language models (LLMs) in representing geometries and their spatial relations. We utilize LLMs including GPT-2 and BERT t...
Modernity and Self-Identity: Self and Society in the Late Modern Age
The reflexivity of modernity extends into core of the self. Put in another way, in the context of a post-traditional order, the self becomes a reflexive project. One concerns th...
Global, regional, and national incidence, prevalence, and years lived with disability for 354 diseases and injuries for 195 countries and territories, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017
The Global Burden of Diseases, Injuries, and Risk Factors Study 2017 (GBD 2017) includes a comprehensive assessment of incidence, prevalence, and years lived with disability (YL...
Knowledge of the Firm, Combinative Capabilities, and the Replication of Technology
How should we understand why firms exist? A prevailing view has been that they serve to keep in check the transaction costs arising from the self-interested motivations of indiv...
Global Consequences of Land Use
Land use has generally been considered a local environmental issue, but it is becoming a force of global importance. Worldwide changes to forests, farmlands, waterways, and air ...
Representation Learning: A Review and New Perspectives
The success of machine learning algorithms generally depends on data representation, and we hypothesize that this is because different representations can entangle and hide more...
Squeeze-and-Excitation Networks
The central building block of convolutional neural networks (CNNs) is the convolution operator, which enables networks to construct informative features by fusing both spatial a...
Linear Models and Empirical Bayes Methods for Assessing Differential Expression in Microarray Experiments
The problem of identifying differentially expressed genes in designed microarray experiments is considered. Lonnstedt and Speed (2002) derived an expression for the posterior od...
Generative adversarial networks
Generative adversarial networks are a kind of artificial intelligence algorithm designed to solve the generative modeling problem. The goal of a generative model is to study a c...
Modularity and community structure in networks
Many networks of interest in the sciences, including social networks, computer networks, and metabolic and regulatory networks, are found to divide naturally into communities or...