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Found 7 papers, 4 papers with code
Approximate sampling and estimation of partition functions using neural networks
We consider the closely related problems of sampling from a distribution known up to a normalizing constant, and estimating said normalizing constant.
Belief propagation for permutations, rankings, and partial orders
Many datasets give partial information about an ordering or ranking by indicating which team won a game, which item a user prefers, or who infected whom.
Belief propagation for networks with loops
Belief propagation is a widely used message passing method for the solution of probabilistic models on networks such as epidemic models, spin models, and Bayesian graphical models, but it suffers from the serious shortcoming that it works poorly in the common case of networks that contain short loops.
Bayesian inference of network structure from unreliable data
Most empirical studies of complex networks do not return direct, error-free measurements of network structure.
Social and Information Networks Physics and Society Applications
Recovering the past states of growing trees
In principle one can reconstruct the past states of a growing network from only its current state.
Social and Information Networks Physics and Society
Improved mutual information measure for classification and community detection
The information theoretic quantity known as mutual information finds wide use in classification and community detection analyses to compare two classifications of the same set of objects into groups.
Mixing patterns and individual differences in networks
We study mixing patterns in networks, meaning the propensity for nodes of different kinds to connect to one another.
Social and Information Networks Physics and Society
