Due to the much smaller volume of anchors, this could significantly reduce the computational complexity of clustering algorithms. Building upon this idea, in this paper, we propose a fast anchor graph ...

a consensus structured bipartite graph proximity matrix is obtained. At the same time, an efficient solution algorithm is proposed for this model. The model's efficacy is underscored through rigorous ...

Markov Affinity-based Graph Imputation of Cells (MAGIC) is an algorithm for denoising high-dimensional data ... elucidating the epithelial-to-mesenchymal transition, read our publication in Cell.

This is a project on segmenting hindi and other Indian languages for easier translation and convenience in other nlp tasks.

Industries from retail to finance are using clustering to personalize services, detect fraud, monitor equipment and improve ...

Proteins are among the most studied molecules in biology, yet new research from the University of Göttingen shows they can ...

Teaching AI to explore its surroundings is a bit like teaching a robot to find treasure in a vast maze—it needs to try different paths, but some lead nowhere. In many real-world challenges, like ...

A review by researchers at Tongji University and the University of Technology Sydney published in Frontiers of Computer Science, highlights the powerful role of graph neural networks (GNNs) in ...

Extensive industrial catalytic applications have shown that the confined nano-channels of zeolites can precisely regulate molecular diffusion and metal cluster migration, effectively enhancing ...