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pro vyhledávání: '"Harary, Marc"'
Though multiple instance learning (MIL) has been a foundational strategy in computational pathology for processing whole slide images (WSIs), current approaches are designed for traditional hematoxylin and eosin (H&E) slides rather than emerging mult
Externí odkaz:
http://arxiv.org/abs/2411.08975
Autor:
Harary, Marc
Robust correlation analysis is among the most critical challenges in statistics. Herein, we develop an efficient algorithm for selecting the $k$- subset of $n$ points in the plane with the highest coefficient of determination $\left( R^2 \right)$. Dr
Externí odkaz:
http://arxiv.org/abs/2410.09316
Kirigami: large convolutional kernels improve deep learning-based RNA secondary structure prediction
Autor:
Harary, Marc, Zhang, Chengxin
We introduce a novel fully convolutional neural network (FCN) architecture for predicting the secondary structure of ribonucleic acid (RNA) molecules. Interpreting RNA structures as weighted graphs, we employ deep learning to estimate the probability
Externí odkaz:
http://arxiv.org/abs/2406.02381
Autor:
Harary, Marc
Reliably measuring the collinearity of bivariate data is crucial in statistics, particularly for time-series analysis or ongoing studies in which incoming observations can significantly impact current collinearity estimates. Leveraging identities fro
Externí odkaz:
http://arxiv.org/abs/2405.14686
Autor:
Harary, Marc
We introduce Secure Haplotype Imputation Employing Local Differential privacy (SHIELD), a program for accurately estimating the genotype of target samples at markers that are not directly assayed by array-based genotyping platforms while preserving t
Externí odkaz:
http://arxiv.org/abs/2309.07305
Autor:
Harary, Marc
RNA secondary structure prediction via deep learning.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9be1212320b764ba74e31bddc1be316a