Interpretability in deep learning for finance: A case study for the Heston model

Deep learning is increasingly used in financial modeling, but its lack of transparency raises risks. Using the well-known ...
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, ...
North Penn Now

Machine Learning Development Company Selection Framework for 2026

Below is a curated list of machine learning development providers that stand out in 2026 for their ability to build enterprise-grade ML solutions tailored to complex business environments.
Nasdaq

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 ...
Opinion
2UrbanGirls on MSNOpinion

Neel Somani on formal methods and the future of machine learning safety

Neel Somani has built a career that sits at the intersection of theory and practice. His work spans formal methods, mac ...