There is more than one way to describe a water molecule, especially when communicating with a machine learning (ML) model, says chemist Robert DiStasio. You can feed the algorithm the molecule's ...

Fraud detection is defined by a structural imbalance that has long challenged data-driven systems. Fraudulent transactions typically account for a fraction of a percent of total transaction volume, ...

Multimodal Learning, Deep Learning, Financial Statement Analysis, LSTM, FinBERT, Financial Text Mining, Automated Interpretation, Financial Analytics Share and Cite: Wandwi, G. and Mbekomize, C. (2025 ...

Foundation models are AI systems trained on vast amounts of data — often trillions of individual data points — and they are capable of learning new ways of modeling information and performing a range ...

Two leading professors from the University of Surrey’s School of Computer Science and Electronic Engineering have been elected Fellows of the Institute of Electrical and Electronics Engineers (IEEE), ...

The study points up interpretability as a critical barrier to trust and adoption. Many AI-based cybersecurity tools function ...

Researchers in Slovakia have demonstrated a machine-learning framework that predicts PV inverter output and detects anomalies using only electrical and temporal data, achieving 100% accuracy in ...

What impressed judges was not only the sophistication of the underlying models, but also Bloomberg’s consistent demonstration ...

The BCTVNet neural network provides accurate and rapid target volume delineation for cervical cancer brachytherapy ...

Lyophilization model can help optimize freeze-drying steps for continuous manufacturing processes, according to MIT researchers.

In a study published in Frontiers in Science, scientists from Purdue University and the Georgia Institute of Technology ...

Acute systemic inflammation has long been suspected to trigger harmful processes within the brain, contributing to ...