2025 Poster "interpretable machine learning" Papers
3 papers found
Causally Reliable Concept Bottleneck Models
Giovanni De Felice, Arianna Casanova Flores, Francesco De Santis et al.
NeurIPS 2025posterarXiv:2503.04363
5
citations
From GNNs to Trees: Multi-Granular Interpretability for Graph Neural Networks
Jie Yang, Yuwen Wang, Kaixuan Chen et al.
ICLR 2025posterarXiv:2505.00364
3
citations
MIX: A Multi-view Time-Frequency Interactive Explanation Framework for Time Series Classification
Viet-Hung Tran, Ngoc Phu Doan, Zichi Zhang et al.
NeurIPS 2025poster