High-performance reactive message-passing based Bayesian inference engine
- Updated
May 5, 2025 - Julia
High-performance reactive message-passing based Bayesian inference engine
The FactorGraph package provides the set of different functions to perform inference over the factor graph with continuous or discrete random variables using the belief propagation algorithm.
Bayesian inference on wiring diagrams.
An MPI-based distributed map-reduce function for Julia
LCM type definitions for compatibility with RobotLocomotion/Drake in Julia
LCM type definitions for compatibility with openhumanoids/bot_core_lcmtypes in Julia
ForneyLab.jl factor node for a nonlinear latent autoregressive model with exogenous input.
ForneyLab.jl factor node for a nonlinear autoregressive model with exogenous input.
ForneyLab.jl factor node for a latent autoregressive model with exogenous input.
Factor graphs based on IndexedGraphs.jl
Concurrent execution of long-running tasks
Add a description, image, and links to the message-passing topic page so that developers can more easily learn about it.
To associate your repository with the message-passing topic, visit your repo's landing page and select "manage topics."