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Reversible MCMC on Markov equivalence classes of sparse directed acyclic graphs
Sparse graphical model Reversible Markov chain Markov equivalence class
2016/1/20
Graphical models are popular statistical tools which are used to represent dependent or causal complex systems. Statistically equivalent causal or directed graphical models are said to belong to a Mar...
Gibbs Measures and Phase Transitions on Sparse Random Graphs
Random graphs Ising model Gibbs measures Phase transitions Spin models Local weak convergence
2015/8/20
Many problems of interest in computer science and information theory can be phrased in terms of a probability distribution over discrete variables associated to the vertices of a large (but finite) sp...
Reversible MCMC on Markov equivalence classes of sparse directed acyclic graphs
Sparse graphical model Reversible Markovchain Markov equivalence class.
2012/11/23
Graphical models are popular statistical tools which are used to represent dependent or causal complex systems. Statistically equivalent causal or directed graphical models are said to belong to a Mar...
Link Prediction in Graphs with Autoregressive Features
Autoregressive Features Link Prediction Graphs
2012/11/22
In the paper, we consider the problem of link prediction in time-evolving graphs. We assume that certain graph features, such as the node degree, follow a vector autoregressive (VAR) model and we prop...
Changepoint Detection over Graphs with the Spectral Scan Statistic
Changepoint Detection over Graphs the Spectral Scan Statistic Statistics Theory
2012/6/21
We consider the change-point detection problem of deciding, based on noisy measurements, whether an unknown signal over a given graph is constant or is instead piecewise constant over two connected in...
Isoradial graphs are a natural generalization of regular graphs which give,for many models of statistical mechanics, the right framework for studying models at criticality.
Description of stochastic and chaotic series using visibility graphs
Data Analysis, Statistics and Probability (physics.data-an) Chaotic Dynamics (nlin.CD)
2010/11/10
Nonlinear time series analysis is an active field of research that studies the structure of complex signals in order to derive information of the process that generated those series, for understanding...