Don't be fooled: label leakage in explanation methods and the importance
of their quantitative evaluation

Don't be fooled: label leakage in explanation methods and the importance of their quantitative evaluation

24 February 2023

Rajesh Ranganath

Papers citing "Don't be fooled: label leakage in explanation methods and the importance of their quantitative evaluation"

11 / 11 papers shown

Title
Explanations that reveal all through the definition of encoding A. Puli Nhi Nguyen Rajesh Ranganath FAtt XAI 31 1 0 04 Nov 2024
Local Feature Selection without Label or Feature Leakage for Interpretable Machine Learning Predictions Harrie Oosterhuis Lijun Lyu Avishek Anand FAtt 35 1 0 16 Jul 2024
Adaptive Sampling of k-Space in Magnetic Resonance for Rapid Pathology Prediction Chen-Yu Yen Raghav Singhal Umang Sharma Rajesh Ranganath S. Chopra Lerrel Pinto 19 1 0 06 Jun 2024
Explaining Time Series via Contrastive and Locally Sparse Perturbations Zichuan Liu Yingying Zhang Tianchun Wang Zefan Wang Dongsheng Luo ... Min Wu Yi Wang Chunlin Chen Lunting Fan Qingsong Wen 19 10 0 16 Jan 2024
Fast Shapley Value Estimation: A Unified Approach Borui Zhang Baotong Tian Wenzhao Zheng Jie Zhou Jiwen Lu TDI FAtt 14 1 0 02 Nov 2023
Towards Robust Fidelity for Evaluating Explainability of Graph Neural Networks Xu Zheng Farhad Shirani Tianchun Wang Wei Cheng Zhuomin Chen Haifeng Chen Hua Wei Dongsheng Luo 24 7 0 03 Oct 2023
Beyond Single-Feature Importance with ICECREAM M.-J. Oesterle Patrick Blobaum Atalanti A. Mastakouri Elke Kirschbaum CML 14 1 0 19 Jul 2023
Explaining Predictive Uncertainty with Information Theoretic Shapley Values David S. Watson Joshua O'Hara Niek Tax Richard Mudd Ido Guy TDI FAtt 13 13 0 09 Jun 2023
FastSHAP: Real-Time Shapley Value Estimation N. Jethani Mukund Sudarshan Ian Covert Su-In Lee Rajesh Ranganath TDI FAtt 56 120 0 15 Jul 2021
Have We Learned to Explain?: How Interpretability Methods Can Learn to Encode Predictions in their Interpretations N. Jethani Mukund Sudarshan Yindalon Aphinyanagphongs Rajesh Ranganath FAtt 73 54 0 02 Mar 2021
Densely Connected Convolutional Networks Gao Huang Zhuang Liu L. V. D. van der Maaten Kilian Q. Weinberger PINN 3DV 244 35,884 0 25 Aug 2016