A machine learning model incorporating functional assessments predicts one-year mortality in older patients with HF and improves risk stratification beyond established scores. Functional status at ...

Heteroscedasticity describes a situation where risk (variance) changes with the level of a variable. In financial models, this means volatility is not constant. Most pricing and forecasting models ...

The reason for this shift is simple: data gravity. The core holds the most complete, consistent and authoritative dataset ...

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions ...

According to A Survey of AI-Enabled Predictive Maintenance for Railway Infrastructure: Models, Data Sources, and Research Challenges, published in Sensors, AI-based predictive maintenance systems ...

Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression with pseudo-inverse training implemented using JavaScript. Compared to other training techniques, such as ...

As well as behavioural and technical issues, firms must also solve a variety of organisational problems to make AI work for ...

The agent acquires a vocabulary of neuro-symbolic concepts for objects, relations, and actions, represented through a ...

A call to reform AI model-training paradigms from post hoc alignment to intrinsic, identity-based development.

Along with the Cross Training equipment, Peloton launched Peloton IQ, its new AI software that gives members a more ...

As global carriers in aggressively pursue AI-driven automation, U.S. operators require architectural frameworks that enable innovation and manage infrastructure.

From fine-tuning open source models to building agentic frameworks on top of them, the open source world is ripe with ...