Published November 10, 2025 | Version v1
Technical note Open

Technical Appendix to "ShapBPT: Image Feature Attributions using Data-Aware Binary Partition Trees"

Authors/Creators

  • 1. ROR icon University of Turin
  • 2. Rulex Innovation Labs
  • 3. Impara Srl
  • 4. Rulex

Description

This is the Technical Appendix for paper "ShapBPT: Image Feature Attributions using Data-Aware Binary Partition Trees", accepted at AAAI-2026 conference.

Files

AAAI26_ShapBPT_Technical_Appendix.pdf

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Additional details

Funding

European Commission
DistriMuSe - DISTRIBUTED MULTI-SENSOR SYSTEMS FOR HUMAN SAFETY AND HEALTH 101139769

Dates

Accepted
2026-11-10
Technical Appendix

Software

Repository URL
https://github.com/amparore/shap_bpt