Here is a list of papers that our speakers and participants flagged as interesting for wider reading in Graphs, Networks, and meaningful applications.

  • Abebe, Rediet & Kleinberg, Jon & Weinberg, S.. (2020). Subsidy Allocations in the Presence of Income Shocks. Proceedings of the AAAI Conference on Artificial Intelligence. 34. 7032-7039. https://www.cs.cornell.edu/~red/AbebeShocks.pdf
  • Maria Chikina, Alan Frieze, Jonathan Mattingly, and Wesley Pegden, “Practical tests for significance in Markov Chains.” ArXiv: Probability (2019) https://arxiv.org/abs/1904.04052
  • Daryl DeFord, Moon Duchin, and Justin Solomon, “Recombination: A family of Markov chains for redistricting.” ArXiv abs/1911.05725 (2019) https://mggg.org/uploads/ReCom.pdf
  • DiMaggio, Paul, and Filiz Garip. “How Network Externalities Can Exacerbate Intergroup Inequality.” American Journal of Sociology, vol. 116, no. 6, 2011, pp. 1887–1933. JSTOR, http://www.jstor.org/stable/10.1086/659653
  • Leventhal, G., Hill, A., Nowak, M. et al. Evolution and emergence of infectious diseases in theoretical and real-world networks. Nat Commun 6, 6101 (2015). https://doi.org/10.1038/ncomms7101
  • Shah, Chintan et al. “Finding Patient Zero: Learning Contagion Source with Graph Neural Networks.” ArXiv abs/2006.11913 (2020): n. pag. https://arxiv.org/abs/2006.11913