scSMD
✨ Generative ModelsResNet-based Clustering
ResNet autoencoder with mutual information clustering for single-cell analysis
Publications
scSMD: Single-cell clustering via mutual information with ResNet
CNN-based Clustering via Mutual Information
scSMD reshapes gene expression as 2D images and uses ResNet autoencoders with mutual information-based clustering
Main Idea
Leverage CNN architectures by treating gene expression as 2D data, clustering via maximizing mutual information with reconstruction
Key Components
ResNet Encoder
2D CNN-based feature extraction from reshaped genes
Mutual Information
Clustering by maximizing MI between data and clusters
ResNet Decoder
Reconstructs 2D gene expression via transposed convolutions
NB Loss
Negative Binomial reconstruction loss
Mathematical Formulation
Loss Functions
Data Flow
Expression → Reshape 2D → ResNet Encoder → MI Clustering → ResNet Decoder → Reconstructed Expression
Architecture Details
Architecture Type
2D CNN Autoencoder with ResNet (VAE Architecture)
Input/Output Types
single-cell → reconstruction