Factor graphs are graphical models with origins in coding theory. The sum-product and the max-product algorithms, which operate by message passing in a factor graph, subsume a great variety of algorithms in coding, signal processing, and artificial intelligence. In this paper, factor graphs are used to express a one-to-one correspondence (based on results by Dennis) between a class of static electrical circuits andmulti-variable probability distributions; these factor graphs may also be viewed as variational representations of the electrical networks. For the classical linear state space models, both the sum-product algorithm and the max-product algorithm coincide with Kalman filtering. By the mentioned correspondence, these algorithms have...
Message passing on a factor graph is a powerful paradigm for the coding of approximate inference alg...
Factor graphs and message passing allow the near-automated development of algorithms in many enginee...
This paper reports on the development of a network analysis technique employing both a linear graph ...
Concepts which promise to extend many fundamental results of network theory to general systems are i...
Complex modern day systems are often characterized by the presence of many interacting variables tha...
Signal flow graphs are combinatorial models for linear dynamical systems, playing a foundational rol...
Signal flow graphs are combinatorial models for linear dynamical systems, playing a foundational rol...
Factor graphs provide a convenient framework for automatically generating (approximate) Bayesian inf...
Factor graphs provide a convenient framework for automatically generating (approximate) Bayesian inf...
Factor graphs provide a convenient framework for automatically generating (approximate) Bayesian inf...
part : TC 1: Foundations of Computer ScienceInternational audienceSignal flow graphs are combinatori...
We use the framework of ``props" to study electrical circuits, signal-flow diagrams, and bond graphs...
We use the framework of ``props" to study electrical circuits, signal-flow diagrams, and bond graphs...
We often encounter probability distributions given as unnormalized products of non-negative function...
Factor graphs provide a convenient framework for automatically generating (approximate) Bayesian inf...
Message passing on a factor graph is a powerful paradigm for the coding of approximate inference alg...
Factor graphs and message passing allow the near-automated development of algorithms in many enginee...
This paper reports on the development of a network analysis technique employing both a linear graph ...
Concepts which promise to extend many fundamental results of network theory to general systems are i...
Complex modern day systems are often characterized by the presence of many interacting variables tha...
Signal flow graphs are combinatorial models for linear dynamical systems, playing a foundational rol...
Signal flow graphs are combinatorial models for linear dynamical systems, playing a foundational rol...
Factor graphs provide a convenient framework for automatically generating (approximate) Bayesian inf...
Factor graphs provide a convenient framework for automatically generating (approximate) Bayesian inf...
Factor graphs provide a convenient framework for automatically generating (approximate) Bayesian inf...
part : TC 1: Foundations of Computer ScienceInternational audienceSignal flow graphs are combinatori...
We use the framework of ``props" to study electrical circuits, signal-flow diagrams, and bond graphs...
We use the framework of ``props" to study electrical circuits, signal-flow diagrams, and bond graphs...
We often encounter probability distributions given as unnormalized products of non-negative function...
Factor graphs provide a convenient framework for automatically generating (approximate) Bayesian inf...
Message passing on a factor graph is a powerful paradigm for the coding of approximate inference alg...
Factor graphs and message passing allow the near-automated development of algorithms in many enginee...
This paper reports on the development of a network analysis technique employing both a linear graph ...