Bethe States of Random Factor Graphs
Sign Up to like & getrecommendations! Published in 2019 at "Communications in Mathematical Physics"
DOI: 10.1007/s00220-019-03387-7
Abstract: We verify a key component of the replica symmetry breaking hypothesis put forward in the physics literature (Mézard and Montanari in Information, physics and computation. Oxford University Press, Oxford, 2009) on random factor graph models.… read more here.
Keywords: random factor; physics; states random; bethe states ... See more keywords
Linear Optimal Control on Factor Graphs — A Message Passing Perspective —
Sign Up to like & getrecommendations! Published in 2017 at "IFAC-PapersOnLine"
DOI: 10.1016/j.ifacol.2017.08.914
Abstract: Abstract Factor graphs form a class of probabilistic graphical models representing the factorization of probability density functions as bipartite graphs. They can be used to exploit the conditional independence structure of the underlying model to… read more here.
Keywords: control; message passing; factor; optimal control ... See more keywords
MICAL: Mutual Information-Based CNN-Aided Learned Factor Graphs for Seizure Detection From EEG Signals
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2023.3252897
Abstract: We develop a hybrid model-based data-driven seizure detection algorithm called Mutual Information-based CNN-Aided Learned factor graphs (MICAL) for detection of eclectic seizures from EEG signals. Our proposed method contains three main components: a neural mutual… read more here.
Keywords: mutual information; cnn; detection; factor graphs ... See more keywords
Handling Constrained Optimization in Factor Graphs for Autonomous Navigation
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Robotics and Automation Letters"
DOI: 10.1109/lra.2022.3228175
Abstract: Factor graphs are graphical models used to represent a wide variety of problems across robotics, such as Structure from Motion (SfM), Simultaneous Localization and Mapping (SLAM) and calibration. Typically, at their core, they have an… read more here.
Keywords: methodology; factor; factor graphs; autonomous navigation ... See more keywords
Belief Propagation, Bethe Approximation and Polynomials
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Transactions on Information Theory"
DOI: 10.1109/tit.2019.2901854
Abstract: Factor graphs are important models for succinctly representing probability distributions in machine learning, coding theory, and statistical physics. Several computational problems, such as computing marginals and partition functions, arise naturally when working with factor graphs.… read more here.
Keywords: bethe approximation; belief propagation; approximation; factor graphs ... See more keywords