Results 231 to 240 of about 1,067,198 (282)
FBL directly binds to and stabilizes SIRT1 by blocking its ubiquitin‐proteasome degradation, thereby sustaining nicotinamide metabolism and redox homeostasis to counteract cellular senescence in ESCC. Genetic and pharmacological suppression of FBL sensitizes tumor cells to senolytic therapy.
Xing Jin +9 more
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Graph neural networks and belief rule base collaborative modeling for automated and interpretable fault diagnosis in proton exchange membrane fuel cells. [PDF]
Zhao Y, Wang T, Wang X.
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Butterfly wing–inspired intrinsically self‐healing polymer interlayers enable flexible perovskite optoelectronics with high luminance, strain‐insensitive stability, and environmental resilience. These hierarchically structured films redistribute mechanical stress, suppress defect formation, and maintain performance under repeated bending, paving the ...
Loganathan Veeramuthu +13 more
wiley +1 more source
Perceptually AMQE-QLDPC coding for quantum image transmission over amplitude-damping channels. [PDF]
Al-Hinai M, Asif HM, Kausar F.
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Optimization by decoded quantum interferometry. [PDF]
Jordan SP +8 more
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Bayesian Transformers and Higher-Order Graph Matching for Cell Tracking in Serial Tissue Sections. [PDF]
Karami M +5 more
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Higher-order trade-offs in hypergraph community detection. [PDF]
Li J, Schaub MT, Peel L.
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Analog Digital Belief Propagation
We introduce a message passing belief propagation (BP) algorithm for factor graph over linear models that uses messages in the form of Gaussian-like distributions. With respect to the regular Gaussian BP, the proposed algorithm adds two operations to the model, namely the wrapping and the discretization of variables.
Montorsi, Guido, Guido Montorsi
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Computational models of belief propagation [PDF]
In this thesis we aim to gain better understanding on the working of the belief propagation algorithm designed for graphical models in other computational frameworks like the neural systems, as well as the error associated with loopy belief propagation in Bayesian networks.
Ng, Khin Hua
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Hardware-efficient belief propagation
2009 IEEE Conference on Computer Vision and Pattern Recognition, 2009Loopy belief propagation (BP) is an effective solution for assigning labels to the nodes of a graphical model such as the Markov random field (MRF), but it requires high memory, bandwidth, and computational costs. Furthermore, the iterative, pixel-wise, and sequential operations of BP make it difficult to parallelize the computation.
Chia-Kai Liang +4 more
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