2026-09-19T17:25:40Z https://www.ideals.illinois.edu/oai-pmh

oai:www.ideals.illinois.edu:2142/109620 2023-07-11 col_2142_5131 col_2142_14787 com_2142_5130 com_2142_9630 com_2142_234

Koyejo, Sanmi Yin, Jialong 2021-03-05T21:47:27Z 2021-03-05T21:47:27Z 2023-03-05T21:47:41Z 2020-12-18 2020-12 Probabilistic graphical models are a statistical framework for conditionally dependent random variables with dependencies represented by graphs. A traditional method to perform inference over these random variables is Belief Propagation. Belief Propagation can be used to compute an exact solution for non-loopy factor graphs. However, when applied to loopy factor graphs, it only estimates marginal probabilities approximately. In this thesis, we propose a Graph Neural Networks (GNN) approach for belief propagation based on message passing mechanisms. In the proposed approach, representations and other functions are learned by the GNN. We apply this approach to the inference of loopy factor graphs. Furthermore, we show that learned representations and functions can also be generalized to factor graphs with different sizes and structures. The results show that our proposal has promising performance compared to the state of the art. Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2022-12-01 The student, Jialong Yin, accepted the attached license on 2020-12-02 at 05:34. The student, Jialong Yin, submitted this Thesis for approval on 2020-12-02 at 05:42. This Thesis was approved for publication on 2020-12-18 at 10:05. DSpace SAF Submission Ingestion Package generated from Vireo submission #16027 on 2021-03-04 at 16:33:13 Made available in DSpace on 2021-03-05T21:47:27Z (GMT). No. of bitstreams: 2 YIN-THESIS-2020.pdf: 2934723 bytes, checksum: 3fcc198870b1e25ebcf55be9c0153116 (MD5) LICENSE.txt: 4208 bytes, checksum: a5a60040618e2d8c8f31906b777f2752 (MD5) Previous issue date: 2020-12-18 Embargo set by: Seth Robbins for item 117326 Lift date: 2023-03-05T21:47:41Z Reason: Author requested closed access (OA after 2yrs) in Vireo ETD system Author requested closed access (OA after 2yrs) in Vireo ETD system Limited application/pdf http://hdl.handle.net/2142/109620 en Copyright 2020 Jialong Yin Belief Propagation Graph Neural Networks Belief propagation on factor graph neural networks text Thesis Mechanical Sci & Engineering Mechanical Engineering University of Illinois at Urbana-Champaign Thesis M.S.