Results 71 to 80 of about 160,175 (304)
Efficient Belief Propagation List Ordered Statistics Decoding of Polar\n Codes [PDF]
, 2021 Yonatan Urman +2 more
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Belief Propagation Min-Sum Algorithm for Generalized Min-Cost Network Flow
, 2018 Belief Propagation algorithms are instruments used broadly to solve graphical model optimization and statistical inference problems. In the general case of a loopy Graphical Model, Belief Propagation is a heuristic which is quite successful in practice ...
horn +6 more
core +1 more source
Diffusion Tractography Biomarker for Epilepsy Severity in Children With Drug‐Resistant Epilepsy
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective To develop a novel deep‐learning model of clinical DWI tractography that can accurately predict the general assessment of epilepsy severity (GASE) in pediatric drug‐resistant epilepsy (DRE) and test if it can screen diverse neurocognitive impairments identified through neuropsychological assessments.
Jeong‐Won Jeong +7 more
wiley +1 more source
Derived dynamic scheduling for belief propagation decoding of LDPC codes
Electronics LettersAmong numerous dynamic scheduling strategies for low‐density parity‐check codes, many of them are of high complexity due to repetitive computation and ordering of belief residuals.
Xiaotian Xu, Hua Zhou, Jiayi Zhao
doaj +1 more source
Improved Belief Propagation Decoding Algorithms for Surface Codes
IEEE Transactions on Quantum EngineeringQuantum error correction is crucial for universal fault-tolerant quantum computing. Highly accurate and low-time-complexity decoding algorithms play an indispensable role in ensuring quantum error correction works effectively.
Jiahan Chen +3 more
doaj +1 more source
Novel Belief Propagation Algorithm for Stereo Matching With a Robust Cost Computation
IEEE Access, 2019 Stereo matching is a challenging problem in the field of computer vision and has recently received extensive attention. However, the traditional methods are labor intensive and premised on specific conditions.
Chuang Pan, Yiqi Liu, Daoping Huang
doaj +1 more source
Inference Attacks on Genomic Data Based on Probabilistic Graphical Models
Big Data Mining and Analytics, 2020 The rapid progress and plummeting costs of human-genome sequencing enable the availability of large amount of personal biomedical information, leading to one of the most important concerns — genomic data privacy. Since personal biomedical data are highly
Zaobo He, Junxiu Zhou
doaj +1 more source
Graph Belief Propagation Networks
, 2021 With the wide-spread availability of complex relational data, semi-supervised node classification in graphs has become a central machine learning problem. Graph neural networks are a recent class of easy-to-train and accurate methods for this problem that map the features in the neighborhood of a node to its label, but they ignore label correlation ...
Jia, Junteng +3 more
openaire +2 more sources
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective The Gold Coast criteria permit diagnosis of amyotrophic lateral sclerosis (ALS) even without upper motor neuron (UMN) signs. However, whether ALS patients with UMN signs (ALSwUMN) and those without (ALSwoUMN) share similar characteristics and prognoses remains unclear.
Hee‐Jae Jung +7 more
wiley +1 more source
Distributed Convergence Verification for Gaussian Belief Propagation
, 2017 Gaussian belief propagation (BP) is a computationally efficient method to approximate the marginal distribution and has been widely used for inference with high dimensional data as well as distributed estimation in large-scale networks.
Du, Jian +2 more
core +1 more source