Graphs and Complex Networks - BKJackson/BKJackson_Wiki GitHub Wiki

Trees

Degrees of separation on a tree algorithm Siena Duplan

Graphs & Neural Networks

Graph Convolutional Networks Thomas Kipf, Sept. 30, 2016.

Social Relationship Modeling

Relationship modeling networks (NAACL 2016)

NetworkX

NetworkX a Python language software package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks.
NetworkX Documentation
NetworkX Tutorial
Notes from tutorial:
You can create graphs of graphs, graphs of files, graphs of functions, and much more. A node can be any hashable object. Edges are built from pairs of nodes. Edges may have attributes, e.g. G.add_edge(2,3,{'weight':3.1415}), and may be associated with any object x, e.g., G.add_edge(n1, n2, object=x). As an example, n1 and n2 could be protein objects from the RCSB Protein Data Bank, and x could refer to an XML record of publications detailing experimental observations of their interaction. Iterator versions of basic methods (e.g. Graph.edges_iter(), Graph.nodes_iter(), Graph.adjacency_iter()) can save you from creating large lists when you are just going to iterate through them anyway. ... and more

SNAP - Stanford Network Analysis Platform

SNAP Home is a general purpose, high performance system for analysis and manipulation of large networks. The core SNAP library is written in C++ and optimized for maximum performance and compact graph representation. It easily scales to massive networks with hundreds of millions of nodes, and billions of edges.

Misc Courses

Advanced Statistical Network Models - CMU CMU graduate level course. Recent work on infinite-dimensional models of networks is based on the related notions of graph limits and of decomposing symmetric network models into mixtures of simpler ones. This course aims to bring students with a working knowledge of network modeling close to the research frontier.