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Found 4 papers, 2 papers with code
MM-Lego: Modular Biomedical Multimodal Models with Minimal Fine-Tuning
Learning holistic computational representations in physical, chemical or biological systems requires the ability to process information from different distributions and modalities within the same model.
HEALNet -- Hybrid Multi-Modal Fusion for Heterogeneous Biomedical Data
Technological advances in medical data collection such as high-resolution histopathology and high-throughput genomic sequencing have contributed to the rising requirement for multi-modal biomedical modelling, specifically for image, tabular, and graph data.
CGXplain: Rule-Based Deep Neural Network Explanations Using Dual Linear Programs
Rule-based surrogate models are an effective and interpretable way to approximate a Deep Neural Network's (DNN) decision boundaries, allowing humans to easily understand deep learning models.
Feature Synergy, Redundancy, and Independence in Global Model Explanations using SHAP Vector Decomposition
We offer a new formalism for global explanations of pairwise feature dependencies and interactions in supervised models.
