Modeling counterparty risk is computationally challenging because it requires the simultaneous evaluation of all trades between each counterparty under both market and credit risk. We present a ...

Advances in hyperspectral imaging including electron energy loss spectroscopy bring forth the challenges of exploratory and physics-based analysis of multidimensional data sets. The multivariate ...

Eutrophication caused by excess wastewater discharge is recognized as a serious water pollution problem worldwide. To prevent water pollution, biological wastewater treatment has been widely adopted ...

When applying machine learning to trading strategy, two inevitable practical issues are achieving interpretable results and securing robustness to market changes. To overcome these challenges, ...

Neural networks revolutionized machine learning for classical computers: self-driving cars, language translation and even artificial intelligence software were all made possible. It is no wonder, then ...