Spatial Fluid Limits for Stochastic Mobile Networks Max Tschaikowski, Mirco Tribastone IMT School for Advanced Studies Lucca, Italy Abstract We consider Markov models of large-scale networks where nodes are characterized

Source URL: cse.lab.imtlucca.it

20 Years of Combining Compositionality & Concurrency of Stochastic Models Holger Hermanns Universität des Saarland, Saarbrücken

Source URL: www.ips.tu-braunschweig.de

Probabilistic Inference in General Graphical Models through Sampling in Stochastic Networks of Spiking Neurons Dejan Pecevski*, Lars Buesing¤, Wolfgang Maass Institute for Theoretical Computer Science, Graz University o

Source URL: apophenia.wdfiles.com

Stochastic models of protein production with feedback Renaud Dessalles joint work with Vincent Fromion and Philippe Robert INRA Jouy-en-Josas - INRIA Rocquencourt (Fance)

Source URL: www.lesprobabilitesdedemain.fr

Embedding machine learning in formal stochastic models of biological processes Jane Hillston School of Informatics, University of Edinburgh 29th October 2014

Source URL: homepages.inf.ed.ac.uk

Probabilistic Inference in General Graphical Models through Sampling in Stochastic Networks of Spiking Neurons Dejan Pecevski*, Lars Buesing¤, Wolfgang Maass Institute for Theoretical Computer Science, Graz University o

Source URL: www.gatsby.ucl.ac.uk

XXXI International Seminar on Stability Problems for Stochastic Models 23 — 27 April, 2013 Moscow, Russia PRELIMINARY PROGRAM Monday, 22 April

Source URL: www.ipiran.ru

Learning and heterogeneity in DSGE models: An agent-based approach

Source URL: www.macfinrobods.eu

• Economics
• New Keynesian economics
• Macroeconomic model
• Dynamic stochastic general equilibrium
• Representative agent
• Bounded rationality
• Economic model
• Agent

University of Vienna Vienna Graduate School of Economics Empirical Macroeconomics: Models and Methods Spring Semester 2013 Thomas A. Lubik

Source URL: www.vgse.at

• Economics
• Statistics
• Statistical theory
• Dynamic stochastic general equilibrium
• Econometrics
• Bayesian statistics
• Bayesian vector autoregression
• Macroeconomic model
• Bayesian inference
• Bayesian
• Prior probability
• Vector autoregression

Gaussian sampling by local perturbations George Papandreou Department of Statistics University of California, Los Angeles

Source URL: www.stat.ucla.edu

• Statistics
• Statistical models
• Stochastic processes
• Linear filters
• Bayesian statistics
• Estimation theory
• Gibbs sampling
• Normal distribution
• Kalman filter
• Mixture model
• Bayesian network
• Gaussian process