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Journal articles on the topic 'Non-local prior'

Author: Grafiati

Published: 9 March 2023

Last updated: 31 July 2025

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1

Fan, Wenshi, Hancheng Yu, Tianming Chen, and Sheng Ji. "OCT Image Restoration Using Non-Local Deep Image Prior." Electronics 9, no. 5 (2020): 784. http://dx.doi.org/10.3390/electronics9050784.

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In recent years, convolutional neural networks (CNN) have been widely used in image denoising for their high performance. One difficulty in applying the CNN to medical image denoising such as speckle reduction in the optical coherence tomography (OCT) image is that a large amount of high-quality data is required for training, which is an inherent limitation for OCT despeckling. Recently, deep image prior (DIP) networks have been proposed for image restoration without pre-training since the CNN structures have the intrinsic ability to capture the low-level statistics of a single image. However,

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Dong Yayun, 董亚运, 毕笃彦 Bi Duyan, 何林远 He Linyuan, and 马时平 Ma Shiping. "Single Image Dehazing Algorithm Based On Non-Local Prior." Acta Optica Sinica 37, no. 11 (2017): 1110001. http://dx.doi.org/10.3788/aos201737.1110001.

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3

Cha, Geonho, Minsik Lee, Jungchan Cho, and Songhwai Oh. "Non-rigid surface recovery with a robust local-rigidity prior." Pattern Recognition Letters 110 (July 2018): 51–57. http://dx.doi.org/10.1016/j.patrec.2018.03.019.

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Feng, Mingkun, Xiaole Han, and Kai Zheng. "Non-Local Prior Dense Feature Distillation Network for Image Compressive Sensing." Information 15, no. 12 (2024): 773. https://doi.org/10.3390/info15120773.

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Deep learning-based image compressive sensing (CS) methods often suffer from high computational complexity and significant loss of image details in reconstructions. A non-local prior dense feature distillation network (NPDFD-Net) is proposed for image CS. First, the non-local priors of images are leveraged to enhance high-frequency information in the measurements. Second, a discrete wavelet decomposition learning module and an inverse discrete wavelet reconstruction module are designed to reduce information loss and significantly lower computational complexity. Third, a feature distillation me

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Xie, Bin, An Huang, and Hui Huang. "Weighted variational regularization image dehazing algorithm based on non-local prior." Journal of Physics: Conference Series 1345 (November 2019): 022007. http://dx.doi.org/10.1088/1742-6596/1345/2/022007.

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Zhao, Shengrong, Zehua Lyu, Hu Liang, and Mudar Sarem. "A Mixed Non-local Prior Model for Image Super-resolution Reconstruction." Chinese Journal of Electronics 26, no. 4 (2017): 778–83. http://dx.doi.org/10.1049/cje.2016.06.024.

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Kaplan, Adam, Eric F. Lock, and Mark Fiecas. "Bayesian GWAS with Structured and Non-Local Priors." Bioinformatics 36, no. 1 (2019): 17–25. http://dx.doi.org/10.1093/bioinformatics/btz518.

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Abstract Motivation The flexibility of a Bayesian framework is promising for GWAS, but current approaches can benefit from more informative prior models. We introduce a novel Bayesian approach to GWAS, called Structured and Non-Local Priors (SNLPs) GWAS, that improves over existing methods in two important ways. First, we describe a model that allows for a marker’s gene-parent membership and other characteristics to influence its probability of association with an outcome. Second, we describe a non-local alternative model for differential minor allele rates at each marker, in which the null an

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SHANGGUAN, Hong, Yi LIU, Quan ZHANG, and Zhiguo GUI. "Fuzzy diffusion PET reconstruction algorithm based on anatomical non-local means prior." Journal of Computer Applications 33, no. 9 (2013): 2627–30. http://dx.doi.org/10.3724/sp.j.1087.2013.02627.

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WANG Yi-bin, 王一斌, 尹诗白 YIN Shi-bai, and 吕卓纹 L Zhuo-wen. "Underwater image restoration with adaptive background light estimation and non-local prior." Optics and Precision Engineering 27, no. 2 (2019): 499–510. http://dx.doi.org/10.3788/ope.20192702.0499.

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10

Johnson, Valen E., and David Rossell. "On the use of non-local prior densities in Bayesian hypothesis tests." Journal of the Royal Statistical Society: Series B (Statistical Methodology) 72, no. 2 (2010): 143–70. http://dx.doi.org/10.1111/j.1467-9868.2009.00730.x.

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11

Chen, Xiaole, Ruifeng Yang, Chenxia Guo, Shuangchao Ge, Zhihong Wu, and Xibin Liu. "Hyper-Laplacian Regularized Non-Local Low-Rank Prior for Blind Image Deblurring." IEEE Access 8 (2020): 136917–29. http://dx.doi.org/10.1109/access.2020.3010540.

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12

Stille, Maik, and M. Thorsten Buzug. "Metal artifact reduction by projection replacements and non-local prior image integration." Current Directions in Biomedical Engineering 1, no. 1 (2015): 100–103. http://dx.doi.org/10.1515/cdbme-2015-0026.

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AbstractThe presence of high-density objects remains an open problem in medical CT imaging. Data of projections that passing through such objects are dominated by noise. Reconstructed images become less diagnostically conclusive because of pronounced artifacts that manifest as dark and bright streaks. A new reconstruction algorithm is proposed, which incorporates information gained from a prior image. Based on a non-local regularization, these information are used to reduce streaking artifacts. In an iterative scheme, the prior image is transformed in order to match intermediate results of the

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Pan, Liming, Cheng Shi, and Ivan Dokmanic. "A Graph Dynamics Prior for Relational Inference." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 13 (2024): 14508–16. http://dx.doi.org/10.1609/aaai.v38i13.29366.

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Relational inference aims to identify interactions between parts of a dynamical system from the observed dynamics. Current state-of-the-art methods fit the dynamics with a graph neural network (GNN) on a learnable graph. They use one-step message-passing GNNs---intuitively the right choice since non-locality of multi-step or spectral GNNs may confuse direct and indirect interactions. But the effective interaction graph depends on the sampling rate and it is rarely localized to direct neighbors, leading to poor local optima for the one-step model. In this work, we propose a graph dynamics prior

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Datta, Saptati, Riana Guha, Rachael Shudde, and Valen E. Johnson. "Bayes factors functions based on test statistics and non-local moment prior densities." Statistics & Probability Letters 219 (April 2025): 110330. https://doi.org/10.1016/j.spl.2024.110330.

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Hamilton, Alan R., and David G. Behm. "The effect of prior knowledge of test endpoint on non-local muscle fatigue." European Journal of Applied Physiology 117, no. 4 (2017): 651–63. http://dx.doi.org/10.1007/s00421-016-3526-4.

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16

Zhang, Ligang. "Non-parametric spatially constrained local prior for scene parsing on real-world data." Engineering Applications of Artificial Intelligence 93 (August 2020): 103708. http://dx.doi.org/10.1016/j.engappai.2020.103708.

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17

Liu, Kun, Shiping Wang, Linyuan He, Duyan Bi, and Shan Gao. "An image dehazing algorithm based on double priors constraint." MATEC Web of Conferences 189 (2018): 04009. http://dx.doi.org/10.1051/matecconf/201818904009.

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Aiming at the color distortion of the restored image in the sky region, we propose an image dehazing algorithm based on double priors constraint. Firstly, we divided the haze image into sky and non-sky regions. Then the Color-lines prior and dark channel prior are used for estimating the transmission of sky and non-sky regions respectively. After introducing color-lines prior to correct sky regions restored by the dark channel prior, we get an accurate transmission. Finally, the local media mean value and standard deviation are used to refine the transmission to obtain the dehazing image. Expe

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18

Sullivan, James M., and Shi-Fan Chen. "Local primordial non-Gaussian bias at the field level." Journal of Cosmology and Astroparticle Physics 2025, no. 03 (2025): 016. https://doi.org/10.1088/1475-7516/2025/03/016.

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Abstract Local primordial non-Gaussianity (LPNG) couples long-wavelength cosmological fluctuations to the short-wavelength behavior of galaxies. This coupling is encoded in bias parameters including bϕ and b δϕ at linear and quadratic order in the large-scale biasing framework. We perform the first field-level measurement of bϕ and b δϕ using Lagrangian bias and non-linear displacements from N-body simulations. We compare our field level measurements with universality predictions and separate universe results, finding qualitative consistency, but disagreement in detail. We also quantify the in

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19

Qi, Hongyu, Zhenwu Fu, Yang Li, and Bo Han. "Non-local structured adaptive dictionary learning method for seismic waveform inversion." Inverse Problems 40, no. 12 (2024): 125024. https://doi.org/10.1088/1361-6420/ad9774.

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Abstract Full waveform inversion (FWI) is a technique used to estimate subsurface model parameters by minimizing the difference between observed and calculated seismic data. Sparsity-promoting regularization are useful tools for traditional FWI methods to tackle complex subsurface structures. Since the traditional regularization techniques can only impose some fixed priors, it is necessary to develop a regularization strategy to obtain more flexible priors. In this way, we develop a structural sparse representation method that exploits the non-local self-similarity prior of the model, which is

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20

Fu, Chuan, and Bo Du. "Remote Sensing Image Compression Based on the Multiple Prior Information." Remote Sensing 15, no. 8 (2023): 2211. http://dx.doi.org/10.3390/rs15082211.

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Learned image compression has achieved a series of breakthroughs for nature images, but there is little literature focusing on high-resolution remote sensing image (HRRSI) datasets. This paper focuses on designing a learned lossy image compression framework for compressing HRRSIs. Considering the local and non-local redundancy contained in HRRSI, a mixed hyperprior network is designed to explore both the local and non-local redundancy in order to improve the accuracy of entropy estimation. In detail, a transformer-based hyperprior and a CNN-based hyperprior are fused for entropy estimation. Fu

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21

Koura, Mikifumi, Masaki Shiota, Shohei Ueda, et al. "Prognostic impact of prior local therapy in castration-resistant prostate cancer." Japanese Journal of Clinical Oncology 51, no. 7 (2021): 1142–48. http://dx.doi.org/10.1093/jjco/hyab019.

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Abstract Objective This study aimed to reveal the prognostic values of prior local therapy in first-line therapy using androgen receptor-axis targeting agents (abiraterone or enzalutamide) or docetaxel for castration-resistant prostate cancer (CRPC). Methods The study included 303 patients treated with first-line therapy for non-metastatic and metastatic CRPC. The association between prior local therapy and therapeutic outcome including progression-free survival and overall survival was investigated by univariate and multivariate analyses as well as propensity score-matched analysis. Results I

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22

Sheu, Shyh-Yang, Chiou-Fen Shieh, and Ruey-Chyuan Shih. "Detection of a Non-local Seismicity Pattern Prior to Larger-size Earthquakes in Taiwan." Terrestrial, Atmospheric and Oceanic Sciences 13, no. 2 (2002): 125. http://dx.doi.org/10.3319/tao.2002.13.2.125(t).

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23

Satapathy, Sukla, and Rajiv Ranjan Sahay. "Robust depth map inpainting using superpixels and non-local Gauss–Markov random field prior." Signal Processing: Image Communication 98 (October 2021): 116378. http://dx.doi.org/10.1016/j.image.2021.116378.

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24

Jiang, Fei, Guosheng Yin, and Francesca Dominici. "Bayesian Model Selection Approach to Multiple Change-Points Detection with Non-Local Prior Distributions." ACM Transactions on Knowledge Discovery from Data 13, no. 5 (2019): 1–17. http://dx.doi.org/10.1145/3340804.

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25

Sanyal, Nilotpal, Min-Tzu Lo, Karolina Kauppi, et al. "GWASinlps: non-local prior based iterative SNP selection tool for genome-wide association studies." Bioinformatics 35, no. 1 (2018): 1–11. http://dx.doi.org/10.1093/bioinformatics/bty472.

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26

Sreehari, Suhas, S. V. Venkatakrishnan, Jeffrey P. Simmons, Lawrence F. Drummy, and Charles A. Bouman. "Non-local Prior Modeling for Tomographic Reconstruction of Bright Field Transmission Electron Microscopy Images." Microscopy and Microanalysis 21, S3 (2015): 1561–62. http://dx.doi.org/10.1017/s1431927615008582.

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27

Li, Wujing, Yuze Liu, Xianfeng Ou, Jianhui Wu, and Longyuan Guo. "Enhancing Image Clarity: A Non-Local Self-Similarity Prior Approach for a Robust Dehazing Algorithm." Electronics 12, no. 17 (2023): 3693. http://dx.doi.org/10.3390/electronics12173693.

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When light propagates in foggy weather, it is affected and scattered by suspended particles in the air. As a result, images taken in this environment often suffer from blurring, reduced contrast, loss of details, and other issues. The primary challenge in dehazing images is to estimate the transmission coefficient map in the atmospheric degradation model. In this paper, we propose a dehazing algorithm based on the optimization of the “haze-line” prior and non-local self-similarity prior. First, we divided the input haze image into small blocks and used the nearest neighbor classification algor

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Han, Ruyi, Shenghai Liao, Shujun Fu та Xingzhou Wang. "Transformed sparsity-boosted low-rank model for image inpainting with non-convex γ-norm regularization and non-local prior". Optics & Laser Technology 181 (лютий 2025): 111865. http://dx.doi.org/10.1016/j.optlastec.2024.111865.

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29

He, Chengxun, Le Sun, Wei Huang, Jianwei Zhang, Yuhui Zheng, and Byeungwoo Jeon. "TSLRLN: Tensor subspace low-rank learning with non-local prior for hyperspectral image mixed denoising." Signal Processing 184 (July 2021): 108060. http://dx.doi.org/10.1016/j.sigpro.2021.108060.

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30

Sarkar, Sourish, and Rajiv Ranjan Sahay. "A Non-Local Superpatch-Based Algorithm Exploiting Low Rank Prior for Restoration of Hyperspectral Images." IEEE Transactions on Image Processing 30 (2021): 6335–48. http://dx.doi.org/10.1109/tip.2021.3093780.

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31

Tayal, Aditya, Pascal Poupart, and Yuying Li. "Hierarchical Double Dirichlet Process Mixture of Gaussian Processes." Proceedings of the AAAI Conference on Artificial Intelligence 26, no. 1 (2021): 1126–33. http://dx.doi.org/10.1609/aaai.v26i1.8309.

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We consider an infinite mixture model of Gaussian processes that share mixture components between non-local clusters in data. Meeds and Osindero (2006) use a single Dirichlet process prior to specify a mixture of Gaussian processes using an infinite number of experts. In this paper, we extend this approach to allow for experts to be shared non-locally across the input domain. This is accomplished with a hierarchical double Dirichlet process prior, which builds upon a standard hierarchical Dirichlet process by incorporating local parameters that are unique to each cluster while sharing mixture

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Zhang, Xiaofeng, Hua Wang, Yan Zhang, Xin Gao, Gang Wang, and Caiming Zhang. "Improved fuzzy clustering for image segmentation based on a low-rank prior." Computational Visual Media 7, no. 4 (2021): 513–28. http://dx.doi.org/10.1007/s41095-021-0239-3.

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AbstractImage segmentation is a basic problem in medical image analysis and useful for disease diagnosis. However, the complexity of medical images makes image segmentation difficult. In recent decades, fuzzy clustering algorithms have been preferred due to their simplicity and efficiency. However, they are sensitive to noise. To solve this problem, many algorithms using non-local information have been proposed, which perform well but are inefficient. This paper proposes an improved fuzzy clustering algorithm utilizing nonlocal self-similarity and a low-rank prior for image segmentation. First

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Rogelj, Peter, and Wassim El-Hajj-Chehade. "Multi-Modality Non-rigid Image Registration Using Local Similarity Estimations." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 29, Supp01 (2021): 31–50. http://dx.doi.org/10.1142/s021848852140002x.

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In this study, we focus on improving the efficiency and accuracy of nonrigid multi-modality registration of medical images. In this regard, we analyze the potentials of using the point similarity measurement approach as an alternative to global computation of mutual information (MI), which is still the most renown multi-modality similarity measure. The improvement capabilities are illustrated using the popular B-spline transformation model. The proposed solution is a combination of three related improvements of the most straightforward implementation, i.e., efficient computation of the voxel d

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Rana, Vishal, Jerusha Fernandes, and Savina Gupta. "Local anaesthesia: Buffered or non-buffered? A comparative study." Indian Journal of Clinical Anaesthesia 9, no. 4 (2022): 450–54. http://dx.doi.org/10.18231/j.ijca.2022.091.

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An ideal local anesthetic should act swiftly and be efficacious without causing discomfort or toxicity. Buffered anesthetic is useful when it comes to limiting toxicity because of the reduced volume that is needed and the decreased time it takes to be effective when compared with other conventional means. Buffered anesthesia uses sodium bicarbonate mixed into lidocaine prior to injection to neutralize the acid. All the patients were explicated about the study and its significance and valid informed consent was procured from those who were willing to participate in the study. Patients were divi

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Zhao, Yao, Decheng Xiao, Zhouhao Pan, Bingo Wing-Kuen Ling, Ye Tian, and Zhe Zhang. "Sparse SAR Imaging Based on Non-Local Asymmetric Pixel-Shuffle Blind Spot Network." Remote Sensing 16, no. 13 (2024): 2367. http://dx.doi.org/10.3390/rs16132367.

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The integration of Synthetic Aperture Radar (SAR) imaging technology with deep neural networks has experienced significant advancements in recent years. Yet, the scarcity of high-quality samples and the difficulty of extracting prior information from SAR data have experienced limited progress in this domain. This study introduces an innovative sparse SAR imaging approach using a self-supervised non-local asymmetric pixel-shuffle blind spot network. This strategy enables the network to be trained without labeled samples, thus solving the problem of the scarcity of high-quality samples. Through

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Tignino, Mara. "Prior Notification and Water Rights." AJIL Unbound 115 (2021): 189–94. http://dx.doi.org/10.1017/aju.2021.23.

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International practice, including international instruments and case law, confirms that states generally accept that they have a duty to provide prior notification of planned measures that may have a significant adverse effect upon co-riparians. The principle of “prior notification” is framed differently in various instruments, and it can broadly include the duty to “notify” and “consult” on planned measures. Prior notification helps to prevent and mitigate disputes, as underlined by the ICJ. Notification and consultation create the conditions for cooperation among riparian states and for ensu

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Bakić, Sonja, Macarena Cuenca-Amigo, and Jaime Cuenca. "Exploring the jazz festival experience amongst local and non-local residents: The case of the Jazzaldia Festival in Spain." International Journal of Event and Festival Management 12, no. 4 (2021): 418–36. https://doi.org/10.1108/IJEFM-05-2021-0037.

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<strong>Purpose </strong>The purpose of this paper is to explore the jazz festival experience at the Heineken Jazzaldia Festival in San Sebastian, Spain. It focuses especially on the relationship between participants’ area of residence and their experience of the festival, concert expectations, preference for different festival settings, and perception of the best aspects of the festival. <strong>Design/methodology/approach </strong>This study modifies and applies the Audience Experience Survey (Radbourne et al., 2009) to the Heineken Jazzaldia Festival in San Sebastian, Spain. A total o

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Cabras, Stefano. "A Dirichlet Process Prior Approach for Covariate Selection." Entropy 22, no. 9 (2020): 948. http://dx.doi.org/10.3390/e22090948.

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The variable selection problem in general, and specifically for the ordinary linear regression model, is considered in the setup in which the number of covariates is large enough to prevent the exploration of all possible models. In this context, Gibbs-sampling is needed to perform stochastic model exploration to estimate, for instance, the model inclusion probability. We show that under a Bayesian non-parametric prior model for analyzing Gibbs-sampling output, the usual empirical estimator is just the asymptotic version of the expected posterior inclusion probability given the simulation outp

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Mameli, Valentina, Debora Slanzi, Jim E. Griffin, and Philip J. Brown. "Multivariate Bayesian Global–Local Shrinkage Methods for Regularisation in the High-Dimensional Linear Model." Mathematics 13, no. 11 (2025): 1812. https://doi.org/10.3390/math13111812.

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This paper considers Bayesian regularisation using global–local shrinkage priors in the multivariate general linear model when there are many more explanatory variables than observations. We adopt priors’ structures used extensively in univariate problems (conjugate and non-conjugate with tail behaviour ranging from polynomial to exponential) and consider how the addition of error correlation in the multivariate set-up affects the performance of these priors. Two different datasets (from drug discovery and chemometrics) with many covariates are used for comparison, and these are supplemented b

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Ren, Chao, Xiaohai He, Yifei Pu, and Truong Q. Nguyen. "Enhanced Non-Local Total Variation Model and Multi-Directional Feature Prediction Prior for Single Image Super Resolution." IEEE Transactions on Image Processing 28, no. 8 (2019): 3778–93. http://dx.doi.org/10.1109/tip.2019.2902794.

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Wang, J., L. Ouyang, W. Lu, and T. Solberg. "SU-E-I-33: Low-Dose CBCT by Iterative Image Reconstruction Using Non-Local Edge-Preserving Prior." Medical Physics 38, no. 6Part4 (2011): 3403. http://dx.doi.org/10.1118/1.3611606.

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Williams, Ryan M., Zachary Cohen, Pooja Vinod Gaikwad, et al. "(Invited) Non-Invasive Injectable Nanotube-Hydrogel Formulations for Local Analyte Detection." ECS Meeting Abstracts MA2024-01, no. 8 (2024): 853. http://dx.doi.org/10.1149/ma2024-018853mtgabs.

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Rapid, minimally-invasive in situ detection of analytes in vivo remains a goal to study inflammatory signaling molecules, disease biomarkers, and pharmacology of therapeutics. To achieve this, we are using the near-infrared fluorescent properties of single-walled carbon nanotubes (SWCNT) to design sensors for use in live mice. SWCNT fluorescence is responsive to the local environment, in the tissue-transparent window, and does not photobleach, allowing for long-term signal monitoring. In this work, we are exploring several formulations of SWCNT embedded within hydrogels which gel in situ. We h

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Han, Bin, Dong Zhou, Moudan Shi, Jie Cao, and Qun Hao. "A Hybrid Variable-Resolution GI without Prior Information." Electronics 13, no. 3 (2024): 595. http://dx.doi.org/10.3390/electronics13030595.

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Ghost imaging (GI) is a novel imaging technique which realizes the fluctuation of the target light field through pattern modulation and obtains the target information in a non-local area. Compared with traditional imaging, GI has the advantages of a simple structure, strong anti-interference ability and imaging resolution beyond the diffraction limit. Illumination patterns are very important for GI, and they are divided into uniform resolution patterns and variable-resolution patterns. The variable-resolution patterns have the characteristics of high resolution in the foveal region and low res

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Navaza, J. "The use of non-local constraints in maximum-entropy electron density reconstruction." Acta Crystallographica Section A Foundations of Crystallography 42, no. 4 (1986): 212–23. http://dx.doi.org/10.1107/s0108767386099397.

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Different expressions of the maximum-entropy estimates of the electron density function, corresponding to different prior information are obtained. They show that no general-purpose configurational entropy of density maps exists. Some universal properties of the modellings are discussed. In particular, the meaning of super-resolution is clarified. The information of lower and upper bounds of the electron density is not in general strong enough to produce atomic maps. Atomicity is then introduced as non-local constraints and applied to the problem of phase extension using experimental data and

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McDonagh, John, Georgios Tzimiropoulos, Kimberley R. Slinger, Zoë J. Huggett, Peter M. Down, and Matt J. Bell. "Detecting Dairy Cow Behavior Using Vision Technology." Agriculture 11, no. 7 (2021): 675. http://dx.doi.org/10.3390/agriculture11070675.

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The aim of this study was to investigate using existing image recognition techniques to predict the behavior of dairy cows. A total of 46 individual dairy cows were monitored continuously under 24 h video surveillance prior to calving. The video was annotated for the behaviors of standing, lying, walking, shuffling, eating, drinking and contractions for each cow from 10 h prior to calving. A total of 19,191 behavior records were obtained and a non-local neural network was trained and validated on video clips of each behavior. This study showed that the non-local network used correctly classifi

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Dijkstra, Madelon, Sanne Nieuwenhuizen, Robbert S. Puijk, et al. "The Role of Neoadjuvant Chemotherapy in Repeat Local Treatment of Recurrent Colorectal Liver Metastases: A Systematic Review and Meta-Analysis." Cancers 13, no. 3 (2021): 378. http://dx.doi.org/10.3390/cancers13030378.

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The additive value of neoadjuvant chemotherapy (NAC) prior to repeat local treatment of patients with recurrent colorectal liver metastases (CRLM) is unclear. A systematic search was performed in PubMed, Embase, Web of Science, and an additional search in Google Scholar to find articles comparing repeat local treatment by partial hepatectomy and/or thermal ablation with versus without NAC. The search included randomized trials and comparative observational studies with univariate/multivariate analysis and/or matching as well as (inter)national guidelines assessed using the AGREE II instrument.

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Graham, Candida R., Sube Banerjee, and Randeep S. Gill. "Using postal questionnaires to identify carer depression prior to initial patient contact." Psychiatric Bulletin 33, no. 5 (2009): 169–71. http://dx.doi.org/10.1192/pb.bp.108.020982.

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Aims and MethodTo assess whether postal questionnaires, used as a local initiative, were useful in identifying carer depression allowing early support for community-dwelling carers of older adults with mental health needs. the Geriatric Depression Scale and a questionnaire collecting information on the carer's circumstances were sent to carers of consecutive patients routinely referred to a community mental health team for older adults in south London. Rates of carer depression between postal questionnaire responders and non-responders were compared.ResultsThe response rate to the postal quest

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Tang, Pingjie, Meng Jiang, Bryan (Ning) Xia, Jed W. Pitera, Jeffrey Welser, and Nitesh V. Chawla. "Multi-Label Patent Categorization with Non-Local Attention-Based Graph Convolutional Network." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 05 (2020): 9024–31. http://dx.doi.org/10.1609/aaai.v34i05.6435.

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Patent categorization, which is to assign multiple International Patent Classification (IPC) codes to a patent document, relies heavily on expert efforts, as it requires substantial domain knowledge. When formulated as a multi-label text classification (MTC) problem, it draws two challenges to existing models: one is to learn effective document representations from text content; the other is to model the cross-section behavior of label set. In this work, we propose a label attention model based on graph convolutional network. It jointly learns the document-word associations and word-word co-oc

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Zhang, Lingli, Li Zeng, and Yumeng Guo. "l0 regularization based on a prior image incorporated non-local means for limited-angle X-ray CT reconstruction." Journal of X-Ray Science and Technology 26, no. 3 (2018): 481–98. http://dx.doi.org/10.3233/xst-17334.

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Xiao, Mian, and WaiChing Sun. "Geometric prior of multi-resolution yielding manifolds and the local closest point projection for nearly non-smooth plasticity." Computer Methods in Applied Mechanics and Engineering 400 (October 2022): 115469. http://dx.doi.org/10.1016/j.cma.2022.115469.

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