Here is a list of papers that our speakers and participants flagged as interesting for wider reading in Graphs, Networks, and meaningful applications. Please feel free to submit more suggestions of papers to share with the community! We will check the form periodically.

  • 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