As energy from the sun reaches Earth, some solar radiation is absorbed by the atmosphere, leading to chemical reactions like ...

AI models use deep learning techniques to analyze patterns in data and generate human-like text based on a user prompt or a ...

We can now collect cell-count data across whole animal brains quantifying recent neuronal activity, gene expression, or anatomical connectivity. This is a powerful approach since it is a multi-region ...

Indra's journey into model risk management began during his time as a data analyst working with predictive models. The ...

In diverse fields of the quantitative sciences, including astronomy, physics, statistics, mathematics and data science, there is a well-established classification of data uncertainties into either ...

Due to the growing reality of global warming and climate change, there is increasing uncertainty around meteorological ...

Objective Systemic lupus erythematosus (SLE) is an autoimmune disease characterised by a loss of immune tolerance, affecting ...

VaR modeling determines the potential for loss in the entity being assessed and the probability of occurrence for the defined loss. One measures VaR by assessing the amount of potential loss, the ...

Analysis of neuroimaging studies shows that close attention to experimental design can increase the statistical robustness of ...

Machine learning and artificial intelligence wouldn't be possible without the statistical models that underpin their analytic capabilities. A Cornell statistician and his colleague have developed a ...

Indra Reddy Mallela is a dedicated Model Risk Manager with extensive experience in compliance, fraud detection, and financial ...

Marketing mix modeling is key to achieving marketing efficiency. Learn its benefits for ROI, channel synergy and data-driven ...