6 citations · 20 across the 8 of their papers we have counts for
5 papers · 1 filter
Measuring Cross-Modal Interactions in Multimodal Models
Laura Wenderoth, Konstantin Hemker, Nikola Simidjievski +1
Integrating AI in healthcare can greatly improve patient care and system efficiency. However, the lack of explainability in AI systems (XAI) hinders their clinical adoption, especi…
Multimodal Lego: Model Merging and Fine-Tuning Across Topologies and Modalities in Biomedicine
Konstantin Hemker, Nikola Simidjievski, Mateja Jamnik
Learning holistic computational representations in physical, chemical or biological systems requires the ability to process information from different distributions and modalities…
HEALNet: Multimodal Fusion for Heterogeneous Biomedical Data
Konstantin Hemker, Nikola Simidjievski, Mateja Jamnik
Technological advances in medical data collection, such as high-throughput genomic sequencing and digital high-resolution histopathology, have contributed to the rising requirement…
CGXplain: Rule-Based Deep Neural Network Explanations Using Dual Linear Programs
Konstantin Hemker, Zohreh Shams, Mateja Jamnik
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 learn…
Feature Synergy, Redundancy, and Independence in Global Model Explanations using SHAP Vector Decomposition
Jan Ittner, Lukasz Bolikowski, Konstantin Hemker +1
We offer a new formalism for global explanations of pairwise feature dependencies and interactions in supervised models. Building upon SHAP values and SHAP interaction values, our…