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, ...
mccormick.northwestern.edu

Trust in Numbers

William Chiu (MSiA '13) works in the fast-paced world of finance, where algorithms often make decisions that impact millions of lives and even more dollars. Now he's helping MLDS students develop ...
The Progress-Index

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

By demonstrating that global interpretability methods can meaningfully reduce the black-box nature of deep learning in finance, the study provides a pathway toward more transparent, trustworthy, and ...