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Found 3 papers, 1 papers with code
Context-Based Multimodal Fusion
Additionally, the network learns to differentiate embeddings of different modalities through fusion with context and aligns data distributions using a contrastive approach for self-supervised learning.
Distributed Collapsed Gibbs Sampler for Dirichlet Process Mixture Models in Federated Learning
Dirichlet Process Mixture Models (DPMMs) are widely used to address clustering problems.
Context Normalization Layer with Applications
Normalization is a pre-processing step that converts the data into a more usable representation.
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