Poster "interpretable machine learning" Papers
14 papers found
Conference
Bayesian Concept Bottleneck Models with LLM Priors
Jean Feng, Avni Kothari, Lucas Zier et al.
NEURIPS 2025arXiv:2410.15555
10
citations
Causally Reliable Concept Bottleneck Models
Giovanni De Felice, Arianna Casanova Flores, Francesco De Santis et al.
NEURIPS 2025arXiv:2503.04363
8
citations
CHiQPM: Calibrated Hierarchical Interpretable Image Classification
Thomas Norrenbrock, Timo Kaiser, Sovan Biswas et al.
NEURIPS 2025arXiv:2511.20779
Differentiable Rule Induction from Raw Sequence Inputs
Kun Gao, Katsumi Inoue, Yongzhi Cao et al.
ICLR 2025
2
citations
Empowering Decision Trees via Shape Function Branching
Nakul Upadhya, Eldan Cohen
NEURIPS 2025arXiv:2510.19040
From GNNs to Trees: Multi-Granular Interpretability for Graph Neural Networks
Jie Yang, Yuwen Wang, Kaixuan Chen et al.
ICLR 2025arXiv:2505.00364
4
citations
MAGE: Model-Level Graph Neural Networks Explanations via Motif-based Graph Generation
Zhaoning Yu, Hongyang Gao
ICLR 2025arXiv:2405.12519
9
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 2025
Compositional Few-Shot Class-Incremental Learning
Yixiong Zou, Shanghang Zhang, haichen zhou et al.
ICML 2024arXiv:2405.17022
21
citations
Local Feature Selection without Label or Feature Leakage for Interpretable Machine Learning Predictions
Harrie Oosterhuis, Lijun Lyu, Avishek Anand
ICML 2024arXiv:2407.11778
3
citations
Post-hoc Part-Prototype Networks
Andong Tan, Fengtao ZHOU, Hao Chen
ICML 2024arXiv:2406.03421
7
citations
Prospector Heads: Generalized Feature Attribution for Large Models & Data
Gautam Machiraju, Alexander Derry, Arjun Desai et al.
ICML 2024arXiv:2402.11729
2
citations
Removing Spurious Concepts from Neural Network Representations via Joint Subspace Estimation
Floris Holstege, Bram Wouters, Noud van Giersbergen et al.
ICML 2024arXiv:2310.11991
3
citations
This Probably Looks Exactly Like That: An Invertible Prototypical Network
Zachariah Carmichael, Timothy Redgrave, Daniel Gonzalez Cedre et al.
ECCV 2024arXiv:2407.12200
6
citations