Bary-GWMDS computes Gromov-Wasserstein barycenters of distance matrices to produce stable consensus embeddings from multi-view relational data, and Mean-GWMDS-C averages distances for reduced-support clustering.
A review on multi-view learning
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A multi-view evidential framework combines semantic and reasoning information to improve accuracy and provide trustworthy uncertainty estimates for mental health prediction on text data.
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Gromov-Wasserstein Methods for Multi-View Relational Embedding and Clustering
Bary-GWMDS computes Gromov-Wasserstein barycenters of distance matrices to produce stable consensus embeddings from multi-view relational data, and Mean-GWMDS-C averages distances for reduced-support clustering.
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Beyond Semantics: An Evidential Reasoning-Aware Multi-View Learning Framework for Trustworthy Mental Health Prediction
A multi-view evidential framework combines semantic and reasoning information to improve accuracy and provide trustworthy uncertainty estimates for mental health prediction on text data.