Open Heart

Enhanced cardiovascular disease risk prediction using integrated machine learning models: a study from the UK Biobank cohort

Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk ...
UC San Diego Today

A New Method to Steer AI Output Uncovers Vulnerabilities and Potential Improvements

A team of researchers has found a way to steer the output of large language models by manipulating specific concepts inside these models. The new method could lead to more reliable, more efficient, ...
TMCnet

Data Normalization vs. Standardization: What's the Difference and When to Use Each

Data Normalization vs. Standardization is one of the most foundational yet often misunderstood topics in machine learning and ...
North Penn Now

Machine Learning Using Python: A Complete Learning Path With Practical Projects

Machine learning is an essential component of artificial intelligence. Whether it’s powering recommendation engines, fraud detection systems, self-driving cars, generative AI, or any of the countless ...
IEEE

Efficient Complex Immittance Spectral Frequency With the Perceptual-Metric-Based Codebook Search

Abstract: Complex-valued frequency-domain linear predictive coding (CLPC) has been developed for audio coding. Recently, representations for efficiently quantizing CLPC coefficients have been proposed ...

Beyond the lakehouse: Fundamental's NEXUS bypasses manual ETL with a native foundation model for tabular data

Emerging from stealth, the company is debuting NEXUS, a Large Tabular Model (LTM) designed to treat business data not as a simple sequence of words, but as a complex web of non-linear relationships.

Fundamental emerges from stealth with first major foundation model trained for tabular data

Emerging from stealth, the company is debuting NEXUS, a Large Tabular Model (LTM) designed to treat business data not as a simple sequence of words, but as a complex web of non-linear relationships.
IEEE

Adaptive Linear Predictive Deadbeat Control Against Machine Parameter Uncertainty of SPMSM Drives for Electric Vehicles

Abstract: A fast and accurate torque/current response is important for optimizing the efficiency of electric vehicles (EVs) and promptly implementing braking instructions in emergencies. Deadbeat ...
Frontiers

The complex impact of auditory error direction, magnitude, and exposure on corrective responses

College of Health Solutions, Arizona State University, Phoenix, AZ, United States Purpose: When encountering errors, the brain produces within-production corrective responses to compensate for the ...