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Found 3 papers, 2 papers with code
Distributed Collapsed Gibbs Sampler for Dirichlet Process Mixture Models in Federated Learning
Dirichlet Process Mixture Models (DPMMs) are widely used to address clustering problems.
MATE-Pred: Multimodal Attention-based TCR-Epitope interaction Predictor
Here, we propose a highly reliable novel method, MATE-Pred, that performs multi-modal attention-based prediction of T-cell receptors and epitopes binding affinity.
Conditional Latent Block Model: a Multivariate Time Series Clustering Approach for Autonomous Driving Validation
The FunCLBM model extends the recently proposed Functional Latent Block Model and allows to create a dependency structure between row and column clusters.
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