ICML "interpretable machine learning" Papers
5 papers found
Compositional Few-Shot Class-Incremental Learning
Yixiong Zou, Shanghang Zhang, haichen zhou et al.
ICML 2024poster
Local Feature Selection without Label or Feature Leakage for Interpretable Machine Learning Predictions
Harrie Oosterhuis, Lijun Lyu, Avishek Anand
ICML 2024poster
Post-hoc Part-Prototype Networks
Andong Tan, Fengtao ZHOU, Hao Chen
ICML 2024poster
Prospector Heads: Generalized Feature Attribution for Large Models & Data
Gautam Machiraju, Alexander Derry, Arjun Desai et al.
ICML 2024poster
Removing Spurious Concepts from Neural Network Representations via Joint Subspace Estimation
Floris Holstege, Bram Wouters, Noud van Giersbergen et al.
ICML 2024poster