Technology Networks

The New Technologies That Could Make Our Food Safer

Advances in analytical chemistry are improving food safety. From mass spectrometry to machine learning and biosensors, ...
technologynetworks

Single-Cell RNA-Seq Data Analysis With AI: Tools, Workflows, and Biological Interpretation

Single-cell RNA-seq AI analysis has become the default way to make sense of the millions of expression measurements a single experiment can now generate. Turning raw sequencing counts into ...
techtimes

Anthropic Hires Berkeley CS Chair Jelani Nelson, Signaling New Phase of AI Race

On Wednesday, Jelani Nelson, a professor of theoretical computer science and chair of UC Berkeley's electrical engineering and computer science division, announced he was taking a leave of absence to ...
International Monetary Fund

Parameter Proliferation in Nowcasting: Issues and Approaches—An Application to Nowcasting China’s Real GDP

This paper evaluates three approaches to address parameter proliferation issue in nowcasting: (i) variable selection using adjusted stepwise autoregressive integrated moving average with exogenous ...
Microsoft

A periodic table for machine learning

Researchers from MIT, Microsoft, and Google have introduced a “periodic table of machine learning” that stands to unify many different machine learning techniques using a single framework. Their ...
IEEE

Dimension Reduction Techniques for Machine Learning-Based AC Microgrid Fault Diagnosis: A Systematic Review

Abstract: The integration of inverter-interfaced sources into microgrids has led to new protection challenges due to fluctuating fault currents, bidirectional power flow, and low inertia. Traditional ...
PNAS

An encoding generative modeling approach to dimension reduction and covariate adjustment in causal inference with observational studies

Causal inference has been increasingly essential in modern observational studies with rich covariate information. However, it is often challenging to estimate the causal effect with high-dimensional ...
Europe PMC

A novel deep machine learning algorithm with dimensionality and size reduction approaches for feature elimination: thyroid cancer diagnoses with randomly missing data.

Thyroid cancer incidences endure to increase even though a large number of inspection tools have been developed recently. Since there is no standard and certain procedure to follow for the thyroid ...
C&EN

Significance of the Chemical Environment of an Element in Nonadiabatic Molecular Dynamics: Feature Selection and Dimensionality Reduction with Machine Learning

Department of Chemical Engineering, University of Southern California, Los Angeles, California 90089, United States Department of Chemistry, University of Southern California, Los Angeles, California ...