ChaosMining: A Benchmark to Evaluate Post-Hoc Local Attribution Methods in Low SNR Environments

17 June 2024

Papers citing "ChaosMining: A Benchmark to Evaluate Post-Hoc Local Attribution Methods in Low SNR Environments"

6 / 6 papers shown

Title
BAGEL: A Benchmark for Assessing Graph Neural Network Explanations Mandeep Rathee Thorben Funke Avishek Anand Megha Khosla 34 14 0 28 Jun 2022
The Disagreement Problem in Explainable Machine Learning: A Practitioner's Perspective Satyapriya Krishna Tessa Han Alex Gu Steven Wu S. Jabbari Himabindu Lakkaraju 172 185 0 03 Feb 2022
HIVE: Evaluating the Human Interpretability of Visual Explanations Sunnie S. Y. Kim Nicole Meister V. V. Ramaswamy Ruth C. Fong Olga Russakovsky 58 114 0 06 Dec 2021
Convolutional Neural Networks Are Not Invariant to Translation, but They Can Learn to Be Valerio Biscione J. Bowers OOD 63 26 0 12 Oct 2021
Densely Connected Convolutional Networks Gao Huang Zhuang Liu L. V. D. van der Maaten Kilian Q. Weinberger PINN 3DV 247 36,356 0 25 Aug 2016
Survey on Feature Selection T. Abdallah B. Iglesia 57 229 0 10 Oct 2015