An avalanche of violence: Analysis reveals predictable patterns in armed conflicts

Phys.org  January 8, 2021 The scaling law proposed in 1941 suggests smaller conflicts are scaled-down versions of bigger ones. This is surprising because one might think that big conflicts and small conflicts are the results of different kinds of processes and social problems. A team of researchers in the US (Santa Fe Institute, Cornell University, Arizona State University) built a new model analyzing data from two decades of armed conflicts in Africa. The dataset includes more than 100,000 events that occurred up to thousands of kilometers apart. They propose a randomly branching armed conflict model to relate the multiple properties […]

How to figure out what you don’t know

TechXplore  October 26, 2020 Machine learning optimizes flexible models to predict data. In scientific applications, there is a rising interest in interpreting these flexible models to derive hypotheses from data. Researchers from Cold Spring Harbor Laboratory tested this connection using a flexible, yet intrinsically interpretable framework for modelling neural dynamics. Many models discovered during optimization predict data equally well, yet they fail to match the correct hypothesis. They developed an alternative approach that identifies models with correct interpretation by comparing model features across data samples to separate true features from noise. Their results reveal that good predictions cannot substitute for […]