Core team:


Jim Bagrow

University of Vermont

Department of Mathematics and Statistics, Assistant Professor

Bagrow's interests include: Complex Networks (community detection, social modeling and human dynamics, statistical phenomena, graph similarity and isomorphism), Statistical Physics (non-equilibrium methods, phase transitions, percolation, interacting particle systems, spin glasses), and Optimization(glassy techniques such as simulated/quantum annealing, (non-gradient) minimization of noisy objective functions).


Most recent papers:


The quoter model: a paradigmatic model of the social flow of written information.

Jim Bagrow, Lewis Mitchell. Chaos: An Interdisciplinary Journal of Nonlinear Science, , 28, 2018.
[pdf] [journal page] [arXiv]

Neural language representations predict outcomes of scientific research.

Jim Bagrow, Daniel Berenberg, Joshua Bongard. Preprint, 2018.
[pdf] [arXiv]

Supporting Material for “Neural language representations predict outcomes of scientific research”.

Jim Bagrow, Daniel Berenberg, Joshua Bongard. Preprint, 2018.
[pdf]

An information-theoretic, all-scales approach to comparing networks.

Jim Bagrow, Erik M. Bollt. Preprint, 2018.
[pdf] [arXiv]

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