Kolmogorov-Arnold networks bridge AI and scientific discovery by increasing interpretability

AI has successfully been applied in many areas of science, advancing technologies like weather prediction and protein folding ...

Predictive Modeling: Techniques, Uses, and Key Takeaways

Discover the power of predictive modeling to forecast future outcomes using regression, neural networks, and more for improved business strategies and risk management.

Interpretable neural networks help reveal the nature of dark matter

A research team from the Xinjiang Astronomical Observatory (XAO) of the Chinese Academy of Sciences has developed an ...
Labmate Online

ELRIG 2025: How Novo Nordisk is showing label-free route to functional phenotyping in brightfield high-content imaging

At ELRIG 2025 Dr Barak Gilboa of Novo Nordisk unveiled a suite of AI-enabled approaches that turn brightfield microscopy from ...
Rail

Platforms demolished as Network Rail provides Huddersfield station update

Platforms 1 and 2 at Huddersfield station have been demolished during the first half of a 30-day closure. The West Yorkshire station has been closed since August 30 and won’t reopen until September 29 ...
Scientific Research Publishing

Genkin, A., Lewis, D.D. and Madigan, D. (2007) Large-Scale Bayesian Logistic Regression for Text Categorization. Technometrics, 49, 291-304.

ABSTRACT: Since transformer-based language models were introduced in 2017, they have been shown to be extraordinarily effective across a variety of NLP tasks including but not limited to language ...
IEEE

Comparative Analysis of Sparse Multinomial Logistic Regression and Convolutional Neural Networks for Multi-Class Image Classification

Abstract: The classification problem represents a funda-mental challenge in machine learning, with logistic regression serving as a traditional yet widely utilized method across various scientific ...
C&EN

RGBChem: Image-Like Representation of Chemical Compounds for Property Prediction

In this work, we introduce RGBChem, a novel approach for converting chemical compounds into image representations, which are subsequently used to train a convolutional neural network (CNN) to predict ...
Frontiers

Predictive modelling employing machine learning, convolutional neural networks (CNNs), and smartphone RGB images for non-destructive biomass estimation of pearl millet ...

Digital tools and non-destructive monitoring techniques are crucial for real-time evaluations of crop output and health in sustainable agriculture, particularly for precise above-ground biomass (AGB) ...