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Found 4 papers, 2 papers with code
Single-Cell Deep Clustering Method Assisted by Exogenous Gene Information: A Novel Approach to Identifying Cell Types
This model leverages exogenous gene network information to facilitate the clustering process, generating discriminative representations.
Single-cell Multi-view Clustering via Community Detection with Unknown Number of Clusters
To this end, we introduce scUNC, an innovative multi-view clustering approach tailored for single-cell data, which seamlessly integrates information from different views without the need for a predefined number of clusters.
Dual-channel Prototype Network for few-shot Classification of Pathological Images
The approach enhances the versatility of prototype representations and elevates the efficacy of prototype networks in few-shot pathological image classification tasks.
TMac: Temporal Multi-Modal Graph Learning for Acoustic Event Classification
We observe that these audiovisual data naturally have temporal attributes, such as the time information for each frame in the video.
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