Abstract: Relation prediction in knowledge graphs is critical for uncovering missing links between entities. Previous models mostly focused on learning the distance of entities and relation within ...

Abstract: Canonical correlation analysis (CCA) has attracted great interest in multi-view representation. However, most of the CCA methods heavily rely on the matrix structure, which may neglect the ...

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Canonical Correlation Analysis Zoo: A collection of Regularized, Deep Learning based, Kernel, and Probabilistic methods in a scikit-learn style framework ...

Biomedical single-cell atlases describe disease at the cellular level. However, analysis of this data commonly focuses on cell-type-centric pairwise cross-condition comparisons, disregarding the ...

Canonicalization is loosely connected to search rankings, but would it be a stretch to call it a ranking factor? You may have heard that the rel=”canonical” tag ...

Emerging single-cell multimodal technologies that simultaneously profile two biological modalities are rapidly being incorporated into biomedical research to obtain a more comprehensive understanding ...

Despite your best effort to implement canonical tags, Google won’t always choose the same URL to display in search results. How can this be fixed? This topic is addressed by Google Search Advocate ...

ABSTRACT: The statistical analysis in Q-methodology is based on factor analysis followed by a factor rotation. Currently, the most common factor extraction methods are centroid and principal component ...