EurekAlert!

Schematic illustration of computation-guided and machine learning (ML)-assisted inorganic materials synthesis. (IMAGE)

The diagram illustrates the interplay among data acquisition, machine learning, and experiment synthesis. Physical models such as thermodynamics and kinetics can be integrated into ML models as expert ...
EurekAlert!

Tensor networks: Enhancing interpretability and efficiency in quantum-inspired machine learning

Deep machine learning has achieved remarkable success in various fields of artificial intelligence, but achieving both high interpretability and high efficiency simultaneously remains a critical ...
Hosted on MSN

Improving the Interpretability of Machine Learning Models

Machine-learning algorithms can make mistakes and be difficult to use, so scientists at the Massachusetts Institute of Technology created explanation methods to assist users in understanding when and ...
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, ...