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  1. Oct 2024
  2. news.mit.edu news.mit.edu
    Modeling relationships to solve complex problems efficiently
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    1. stopresetgo 09 Oct 2024
      focusing on dynamic problems where data in a graph network change over time.When a dataset has billions or trillions of data points, running an algorithm from scratch to make one small change could be extremely expensive from a computational point of view. He and his students design parallel algorithms that process many updates at the same time, improving efficiency while preserving accuracy.

      for - Indyweb dev - dynamic graph networks

      Indyweb dev - dynamic graph networks
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    news.mit.edu/2024/julian-shun-solves-complex-problems-efficiently-1004
  3. Jun 2020
  4. arxiv.org arxiv.org
    Structural Temporal Graph Neural Networks for Anomaly Detection in Dynamic Graphs
    1
    1. edampf 08 Jun 2020

      Cai, L., Chen, Z., Luo, C., Gui, J., Ni, J., Li, D., & Chen, H. (2020). Structural Temporal Graph Neural Networks for Anomaly Detection in Dynamic Graphs. ArXiv:2005.07427 [Cs, Stat]. http://arxiv.org/abs/2005.07427

      is:preprint lang:en anomaly detection dynamic graph neural network StrGNN structural temporal graph neural network model modeling
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    arxiv.org/abs/2005.07427