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Found 6 papers, 5 papers with code
On the Effects of Self-supervision and Contrastive Alignment in Deep Multi-view Clustering
To address this, we present DeepMVC, a unified framework for deep MVC that includes many recent methods as instances.
Hubs and Hyperspheres: Reducing Hubness and Improving Transductive Few-shot Learning with Hyperspherical Embeddings
Distance-based classification is frequently used in transductive few-shot learning (FSL).
RELAX: Representation Learning Explainability
Our approach can also model the uncertainty in its explanations, which is essential to produce trustworthy explanations.
Reconsidering Representation Alignment for Multi-view Clustering
Aligning distributions of view representations is a core component of today's state of the art models for deep multi-view clustering.
Leveraging tensor kernels to reduce objective function mismatch in deep clustering
In this work we study OFM in deep clustering, and find that the popular autoencoder-based approach to deep clustering can lead to both reduced clustering performance, and a significant amount of OFM between the reconstruction and clustering objectives.
Recurrent Deep Divergence-based Clustering for simultaneous feature learning and clustering of variable length time series
The task of clustering unlabeled time series and sequences entails a particular set of challenges, namely to adequately model temporal relations and variable sequence lengths.
