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 ...
pv magazine International

AI now can now predict solar cell efficiency from wafer quality

Korea University researchers have developed a machine-learning framework that predicts solar cell efficiency from wafer quality, enabling early wafer screening and optimized production paths. Using ...
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 ...
Tech Xplore

Study finds 'dosed' nonlinearity can beat linear and fully nonlinear AI

Umbrella or sun cap? Buy or sell stocks? When it comes to questions like these, many people today rely on AI-supported recommendations. Chatbots such as ChatGPT, AI-driven weather forecasts, and ...
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 ...
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 ...