The concept of AI self-improvement has been a hot topic in recent research circles, with a flurry of papers emerging and prominent figures like OpenAI CEO Sam Altman weighing in on the future of ...

This paper examines the utilization of machine learning methods to predict the values of valuable metals, specifically gold, silver, palladium, and platinum, from 2017 to 2023. Accurate price ...

Individual survival and evolutionary selection require biological organisms to maximize reward. Economic choice theories define the necessary and sufficient conditions, and neuronal signals of ...

† Department of Chemical Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139, United States ‡ The Ragon Institute of MGH, MIT, and Harvard, ...

Air pollution is an issue across the world. It not only directly affects the environment and human health, but also influences the regional and even global climate by changing the atmospheric ...

Sequentia is a Python package that provides various classification and regression algorithms for sequential data, including methods based on hidden Markov models and dynamic time warping. Some ...

You are free to share (copy and redistribute) this article in any medium or format and to adapt (remix, transform, and build upon) the material for any purpose, even commercially within the parameters ...

Dynast is a command-line pipeline that preprocesses data from metabolic labeling scRNA-seq experiments and quantifies the following four mRNA species: unlabeled unspliced, unlabeled spliced, labeled ...

Latent variable models (LVMs) are powerful tools for discovering hidden structure in data. Canonical LVMs include factor analysis, which explains the correlation of a large number of observed ...

Recent high throughput experimental methods have been used to collect large biomedical omics datasets. Clustering of single omic datasets has proven invaluable for biological and medical research. The ...