Papers
1–3 of 3Research Paper·Mar 8, 2026
TT-Sparse: Learning Sparse Rule Models with Differentiable Truth Tables
Interpretable machine learning is essential in high-stakes domains where decision-making requires accountability, transparency, and trust. While rule-based models offer global and exact interpretabili...
8.0 viability
Research Paper·Mar 9, 2026
This Looks Distinctly Like That: Grounding Interpretable Recognition in Stiefel Geometry against Neural Collapse
Prototype networks provide an intrinsic case based explanation mechanism, but their interpretability is often undermined by prototype collapse, where multiple prototypes degenerate to highly redundant...
7.0 viability
Research Paper·Feb 23, 2026
Behavior Learning (BL): Learning Hierarchical Optimization Structures from Data
Inspired by behavioral science, we propose Behavior Learning (BL), a novel general-purpose machine learning framework that learns interpretable and identifiable optimization structures from data, rang...
5.0 viability