Variational Bayesian inference for beamforming

The Journal of the Acoustical Society of America ◽

10.1121/10.0007965 ◽

2021 ◽

Vol 150 (4) ◽

pp. A154-A154

Author(s):

Yongsung Park ◽

Florian Meyer ◽

Peter Gerstoft

Keyword(s):

Bayesian Inference ◽

Variational Bayesian ◽

Variational Bayesian Inference

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Probabilistic model updating via variational Bayesian inference and adaptive Gaussian process modeling

Computer Methods in Applied Mechanics and Engineering ◽

10.1016/j.cma.2021.113915 ◽

2021 ◽

Vol 383 ◽

pp. 113915

Author(s):

Pinghe Ni ◽

Jun Li ◽

Hong Hao ◽

Qiang Han ◽

Xiuli Du

Keyword(s):

Bayesian Inference ◽

Gaussian Process ◽

Process Modeling ◽

Probabilistic Model ◽

Model Updating ◽

Variational Bayesian ◽

Variational Bayesian Inference ◽

Gaussian Process Modeling

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Off-grid DOA estimation through variational Bayesian inference in colored noise environment

Digital Signal Processing ◽

10.1016/j.dsp.2021.102967 ◽

2021 ◽

Vol 111 ◽

pp. 102967

Author(s):

Yahao Zhang ◽

Yixin Yang ◽

Long Yang

Keyword(s):

Bayesian Inference ◽

Colored Noise ◽

Doa Estimation ◽

Variational Bayesian ◽

Noise Environment ◽

Variational Bayesian Inference

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Stochastic collapsed variational Bayesian inference for biterm topic model

2016 International Joint Conference on Neural Networks (IJCNN) ◽

10.1109/ijcnn.2016.7727629 ◽

2016 ◽

Author(s):

Narutaka Awaya ◽

Jun Kitazono ◽

Toshiaki Omori ◽

Seiichi Ozawa

Keyword(s):

Bayesian Inference ◽

Topic Model ◽

Variational Bayesian ◽

Variational Bayesian Inference

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Reconstruction-Aware Imaging System Ranking by Use of a Sparsity-Driven Numerical Observer Enabled by Variational Bayesian Inference

IEEE Transactions on Medical Imaging ◽

10.1109/tmi.2018.2880870 ◽

2019 ◽

Vol 38 (5) ◽

pp. 1251-1262 ◽

Author(s):

Yujia Chen ◽

Yang Lou ◽

Kun Wang ◽

Matthew A. Kupinski ◽

Mark A. Anastasio

Keyword(s):

Bayesian Inference ◽

Imaging System ◽

Variational Bayesian ◽

Variational Bayesian Inference

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Skew t Distribution-Based Nonlinear Filter with Asymmetric Measurement Noise Using Variational Bayesian Inference

Computer Modeling in Engineering & Sciences ◽

10.32604/cmes.2021.019027 ◽

2022 ◽

Vol 130 (1) ◽

pp. 1-16

Author(s):

Chen Xu ◽

Yawen Mao ◽

Hongtian Chen ◽

Hongfeng Tao ◽

Fei Liu

Keyword(s):

Bayesian Inference ◽

Nonlinear Filter ◽

Measurement Noise ◽

Variational Bayesian ◽

Variational Bayesian Inference ◽

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Variational Bayesian Inference for Multinomial Dirichlet Gaussian Process Classification Model

Advances in Computer Science and Ubiquitous Computing - Lecture Notes in Electrical Engineering ◽

10.1007/978-981-10-0281-6_117 ◽

2015 ◽

pp. 835-842

Author(s):

Wanhyun Cho ◽

Soonja Kang ◽

Sangkyoon Kim ◽

Soonyoung Park

Keyword(s):

Bayesian Inference ◽

Gaussian Process ◽

Classification Model ◽

Variational Bayesian ◽

Variational Bayesian Inference ◽

Process Classification

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Estimation algorithm for system with non‐Gaussian multiplicative/additive noises based on variational Bayesian inference

International Journal of Adaptive Control and Signal Processing ◽

10.1002/acs.2973 ◽

2019 ◽

Vol 33 (4) ◽

pp. 586-608 ◽

Author(s):

Xingkai Yu ◽

Jianxun Li ◽

Jian Xu

Keyword(s):

Bayesian Inference ◽

Estimation Algorithm ◽

Variational Bayesian ◽

Variational Bayesian Inference ◽

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Multimode Process Monitoring Using Variational Bayesian Inference and Canonical Correlation Analysis

IEEE Transactions on Automation Science and Engineering ◽

10.1109/tase.2019.2897477 ◽

2019 ◽

Vol 16 (4) ◽

pp. 1814-1824 ◽

Author(s):

Qingchao Jiang ◽

Xuefeng Yan

Keyword(s):

Bayesian Inference ◽

Correlation Analysis ◽

Process Monitoring ◽

Canonical Correlation Analysis ◽

Canonical Correlation ◽

Variational Bayesian ◽

Variational Bayesian Inference

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Variational Bayesian inference for the multiple-choice DINA model

Behaviormetrika ◽

10.1007/s41237-020-00104-w ◽

2020 ◽

Vol 47 (1) ◽

pp. 159-187 ◽

Author(s):

Kazuhiro Yamaguchi

Keyword(s):

Bayesian Inference ◽

Multiple Choice ◽

Variational Bayesian ◽

Variational Bayesian Inference ◽

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Learning from Demonstration Using Variational Bayesian Inference

Current Approaches in Applied Artificial Intelligence - Lecture Notes in Computer Science ◽

10.1007/978-3-319-19066-2_36 ◽

2015 ◽

pp. 371-381 ◽

Author(s):

Mostafa Hussein ◽

Yasser Mohammed ◽

Samia A. Ali

Keyword(s):

Bayesian Inference ◽

Learning From Demonstration ◽

Variational Bayesian ◽

Variational Bayesian Inference

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