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https://github.com/biaslab/l4dc-2020

Proof of concept for online hybrid message passing inference for AR-HGF.

https://github.com/biaslab/l4dc-2020

Science Score: 26.0%

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    Low similarity (2.3%) to scientific vocabulary

Keywords

autoregressive factor-graphs hierarchical-models message-passing online-learning-algorithms time-varying
Last synced: 6 months ago · JSON representation

Repository

Proof of concept for online hybrid message passing inference for AR-HGF.

Basic Info
  • Host: GitHub
  • Owner: biaslab
  • Language: Jupyter Notebook
  • Default Branch: master
  • Homepage:
  • Size: 251 MB
Statistics
  • Stars: 0
  • Watchers: 5
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Topics
autoregressive factor-graphs hierarchical-models message-passing online-learning-algorithms time-varying
Created over 6 years ago · Last pushed about 6 years ago
Metadata Files
Readme

README.md

Proof of concept for online hybrid message passing inference for AR-HGF.

To run the experiments from AR-HGF.ipynb you need to install the following packages: - ForneyLab.jl (v0.10.0) - PolynomialRoots.jl - Distributions.jl - FastGaussQuadrature.jl - ForwardDiff.jl - ProgressMeter.jl - LaTeXStrings.jl - DSP.jl - Plots.jl

Owner

  • Name: BIASlab
  • Login: biaslab
  • Kind: organization
  • Email: info@biaslab.org
  • Location: Eindhoven, the Netherlands

Bayesian Intelligent Autonomous Systems lab

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Last synced: 9 months ago

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  • Total Committers: 2
  • Avg Commits per committer: 12.0
  • Development Distribution Score (DDS): 0.083
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  • Avg Commits per committer: 0.0
  • Development Distribution Score (DDS): 0.0
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Last synced: 9 months ago

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Past Year
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