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Code accompanying the minitutorial Tensor Eigenvectors and Stochastic Processes at SIAM ALA 2018.
Jupyter Notebook Julia
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.gitignore
3-node-cycle-walks.ipynb
7-node-line-walks.ipynb
README.md
animate_random_walk.jl
brownian-motion.gif
brownian-motion.pdf
example_common.jl
nbrw-with-dist-on-gnr.gif
polya-distribution.pdf
polya-urn.gif
random_walk_limits.jl
rw-with-dist-on-gnr.gif
srw_failure.jl
stochastic-processes.ipynb

README.md

Julia code and Jupyter notebooks accompanying the Tensor Eigenvectors and Stochastic Processes (TESP) mini-tutorial at SIAM ALA 2018 in Hong Kong.

See http://www.cs.cornell.edu/~arb/tesp for more information on the minitutorial.

This respository contains notebooks and codes for some of the results presented in the tutorial.

Stochastic processes

Jupyter notebook for the examples of stochastic processesare in stochastic-processes.ipynb.

RWs, non-backtracking RWs, and spacey RWs

There are two Jupyter notebooks for the two examples comparing random walks, non-backtracking random walks, and (super) spacey random walks for the 3-node and 7-node graph examples:

  • 3-node-cycle-walks.ipynb
  • 7-node-line-walks.ipynb

Graph random walk animations

Several of the animations for (non-backtracing) random walks are in the script animate_random_walk.jl .

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