Risk Identification & Quantification in Complex Human-Natural Systems via Convergent Data Intensive Research.

Schafer, Toryn L.J.

McGranaghan, Ryan M.

Getmansky Sherman, Mila.

Feng, Mei-Ling E.

Owolabi, Olukunle O.

Ryan, Sean E.

D?ker, Marie-Christine.

Jauch, Michael.

Matteson, David S.

2021

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Description
  • Keywords: associated anomalies, complex systems, data-intensive risk assessment, human-natural systems, systemic risk, volatility.

    Topic: Applied computing

    Topic: Applied computing / Physical sciences and engineering / Mathematics and statistics

    ACM Open.
This object is in collection Permanent URL Citation
  • Toryn L.J. Schafer, et. al. "Risk Identification & Quantification in Complex Human-Natural Systems via Convergent Data Intensive Research." Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining, 2021
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ft849486f
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DOI:
10.1145/3447548.3469480