Mass shooting model identifies firearm availability as key limit on risk

Can mass shootings be forecast? Mohammad R.K. Mofrad and colleagues constructed an agent-based model of mass shootings within ...

Bayesian Inference and Deep Learning: Theory and Practice of Generative Models

IntroductionPurpose of this bookThis book depicts the path from Bayesian inference to deep learning as a single long-form technical volume. There is one central theme: how can we handle uncertainty in ...
BIOENGINEER

Lightweight AI Model Slashes Flood Warning Times by Over 80 Percent

Floods remain among the deadliest and most economically destructive natural hazards on Earth, and the window in which ...
US Geological Survey

Combining conflicting Bayesian models to develop paleoseismic records—An example from the Wasatch Fault Zone, Utah

Authors Christopher B. DuRoss, Scott E.K. Bennett, Richard W. Briggs, Stephen Personius, Ryan D. Gold, Nadine G. Reitman, Adam I. Hiscock, Shannon A. Mahan ...

Your model is 'ignoring' the minority—the true name of class imbalance is Bayesian bias

For some reason, this model won't predict the minority class.”It's frustrating. Many engineers have felt this way.However, ...
US Geological Survey

Marginalizing Bayesian population models - data for examples in the Grand Canyon region, southeastern Arizona, western Oregon USA - 1990-2015

Authors Charles B Yackulic, Maria C Dzul, Jane A Reid, Jamie S. Sanderlin, William M. Block, Joseph L. Ganey, Michael J Dodrill, Mike D Yard ...
Risk.net

Bayesian unsmoothing for private market investments: a probabilistic approach to risk estimation

This paper puts forward a Bayesian unsmoothing method to model smoothing parameters probabilistically which mitigates ...