insideHPC

Machine Learning Interpretability with Driverless AI

Data visualization techniques for representing high-degree interactions and nuanced data structures. Contemporary linear model variants that incorporate machine learning and are appropriate for use in ...
Reuters

Dan Herbatschek Leads New Initiative in New York and Los Angeles to Advance Transparency and Interpretability in Machine Learning

NEW YORK, NY, November 28, 2025 (EZ Newswire) -- Dan Herbatschek, opens new tab, founder and CEO of Ramsey Theory Group, opens new tab, has announced a new initiative to strengthen transparency, ...
Seeking Alpha

NTT Researchers Advance AI and Machine Learning Accuracy, Security and Cost Effectiveness at ICML 2025

NTT Research and NTT R&D scientists presented 12 papers at ICML 2025, one of the world’s most prestigious conferences on AI and machine learning. Three papers co-authored by NTT Research Physics of AI ...

Machine learning can predict patients' responses to antidepressants while disentangling drug and placebo effects

Depression is one of the most widespread mental health disorders worldwide, affecting approximately 4% of the global ...
Quanta Magazine

What Is Machine Learning?

Machine learning is a subfield of artificial intelligence, which explores how to computationally simulate (or surpass) humanlike intelligence. While some AI techniques (such as expert systems) use ...
Devdiscourse

Digital farming push exposes gaps in agricultural data standards

Data quality problems are systemic in agriculture, the researchers note. Historical reliance on local practices, fragmented ...
EurekAlert!

Machine learning-driven predictions of biochar yield and NPK composition: insights into biomass pyrolysis with data augmentation and model interpretability (IMAGE)

Disclaimer: AAAS and EurekAlert! are not responsible for the accuracy of news releases posted to EurekAlert! by contributing institutions or for the use of any information through the EurekAlert ...