Probabilistic programming with stochastic variational message passing

DOI10.1016/j.ijar.2022.06.006OpenAlexW4283718553WikidataQ114171983 ScholiaQ114171983MaRDI QIDQ2169202

İsmail Şenöz, Semih Akbayrak, Alp Sarı, Bert J. M. De Vries

Publication date: 2 September 2022

Published in: International Journal of Approximate Reasoning (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ijar.2022.06.006

zbMATH Keywords

message passingprobabilistic programmingvariational inferencefactor graphsnatural gradient descent

Mathematics Subject Classification ID

Reasoning under uncertainty in the context of artificial intelligence (68T37)

Uses Software

• Stan
• BayesDA
• Julia
• TensorFlow
• DiffSharp
• ForwardDiff
• PyTorch
• Pyro
• ForneyLab
• ADVI
• Turing
• PRMLT

Cites Work

• Information geometry and its applications
• Monte Carlo co-ordinate ascent variational inference
• Graphical Models, Exponential Families, and Variational Inference
• The Variational Gaussian Approximation Revisited
• Rao-Blackwellisation of sampling schemes
• Codes on graphs: normal realizations
• Hierarchical Bayesian Analysis of Changepoint Problems
• Bayesian Reasoning and Machine Learning
• A Stochastic Approximation Method
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