Abstract: We propose an explainable topic modeling method that tracks user interests to elucidate their association with social events while ensuring high reliability and low computational cost.

We present SNPic, a probabilistic framework that redefines the analytical landscape of complex trait genetics. By conceptualizing genetic associations as a highly structured probabilistic language, ...

"/home/anotario/anaconda2/envs/EI_python36/lib/python3.6/site-packages/gensim/models/phrases.py:598: UserWarning: For a faster implementation, use the gensim.models ...

University of Birmingham experts have created open-source computer software that helps scientists understand how fast-moving particles behave when they interact with electromagnetic waves in space.

Part 2 of modeling Faraday’s Law using Python. This tutorial explores electromagnetic induction through code and simulation to better understand changing magnetic fields and induced currents. #physics ...

A behind-the-scenes look at how a Cisco automation engineer replaced fragile CLI workflows with model-driven infrastructure that scales. NEW YORK, NY, UNITED STATES ...

Free-text responses came from 34% (1220/3579) of motivated and 64% (153/240) of neutral participants. Biterm topic modeling revealed motivated participants emphasized early detection benefits, health ...

Understanding and ultimately controlling immune function takes much more than listing cell types, cytokines, and receptors. It requires quantitative ways of thinking and modeling that can capture the ...

Abstract: Topic modeling is widely used approach for identifying latent topics in large textual dataset. For improved topic extraction and representations, this work introduces an advanced topic ...