Sparse Coding and Temporal Pattern Learning Co-Mediated by Dual Spike-Timing-Dependent Plasticity in a Multilayer Excitatory-Inhibitory Spiking Network. [PDF]
Yuan C, Wang D, Li X, Gao X.
europepmc +1 more source
Towards understanding residual and dilated dense neural networks via convolutional sparse coding. [PDF]
Zhang Z, Zhang S.
europepmc +1 more source
A multimodal fusion framework integrating sequence, atomic, and fragment representations captures drug–target interactions across multiple scales. The model delivers strong predictive performance and enables efficient virtual screening. Applied to hematopoietic progenitor kinase 1 (HPK1), it identifies structurally diverse inhibitors with nanomolar ...
Shuo Liu +7 more
wiley +1 more source
Neuronal allocation and sparse coding of episodic memories in the human hippocampus. [PDF]
Tallman CW, Steinmetz PN, Wixted JT.
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Improved Prediction of Imminent Progression to Clinically Significant Memory Decline Using Surface Multivariate Morphometry Statistics and Sparse Coding. [PDF]
Stonnington CM +12 more
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An interpretable, unsupervised artificial intelligence framework identifies a 13‐cellular morphometric biomarker (CMB) signature from routine H&E whole‐slide images. Validated across 2,602 patients, the fixed signature generalizes across colorectal, gastric, and esophageal tissues without retraining, stratifies prognosis and precancerous lesion risk ...
Pin Wang +14 more
wiley +1 more source
A deep dictionary clustering approach for unsupervised image retrieval using convolutional sparse coding. [PDF]
Sucharitha G +6 more
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Clinical intramuscular thymus transplantation yields only short‐lived efficacy and marginal therapeutic benefits. Benefiting from the spleen's intrinsic strengths—rapid vascular perfusion, abundant developmental factors, and resident progenitors—the intrasplenic thymic grafts achieve robust thymic regeneration and substantial T‐cell reconstitution ...
Shaocong Wang +10 more
wiley +1 more source
Sonar image denoising based on clustering and Bayesian sparse coding. [PDF]
Xing C, Bao D, Huang T, Meng Y.
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Predicting Brain Amyloid Using Multivariate Morphometry Statistics, Sparse Coding, and Correntropy: Validation in 1,101 Individuals From the ADNI and OASIS Databases. [PDF]
Wu J +10 more
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