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Found 5 papers, 3 papers with code
Explainable Machine Learning for Predicting Homicide Clearance in the United States
Purpose: To explore the potential of Explainable Machine Learning in the prediction and detection of drivers of cleared homicides at the national- and state-levels in the United States.
BIG-bench Machine Learning
Explainable artificial intelligence
Multi-modal Networks Reveal Patterns of Operational Similarity of Terrorist Organizations
Capturing dynamics of operational similarity among terrorist groups is critical to provide actionable insights for counter-terrorism and intelligence monitoring.
Learning future terrorist targets through temporal meta-graphs
Using real-world data on attacks occurred in Afghanistan and Iraq from 2001 to 2018, we propose the use of temporal meta-graphs and deep learning to forecast future terrorist targets.
Temporal Clustering of Disorder Events During the COVID-19 Pandemic
The COVID-19 pandemic has unleashed multiple public health, socio-economic, and institutional crises.
Where Are We? Using Scopus to Map the Literature at the Intersection Between Artificial Intelligence and Research on Crime
What are the current research trends in terms of topics in this area?
