Q-SENN: Quantized Self-Explaining Neural Networks

21 December 2023

Papers citing "Q-SENN: Quantized Self-Explaining Neural Networks"

7 / 7 papers shown

Title
QPM: Discrete Optimization for Globally Interpretable Image Classification Thomas Norrenbrock T. Kaiser Sovan Biswas R. Manuvinakurike Bodo Rosenhahn 55 0 0 27 Feb 2025
OMENN: One Matrix to Explain Neural Networks Adam Wróbel Mikołaj Janusz Bartosz Zieliñski Dawid Rymarczyk FAtt AAML 75 0 0 03 Dec 2024
What You See is What You Classify: Black Box Attributions Steven Stalder Nathanael Perraudin R. Achanta F. Pérez-Cruz Michele Volpi FAtt 24 9 0 23 May 2022
Interpretable Image Classification with Differentiable Prototypes Assignment Dawid Rymarczyk Lukasz Struski Michal Górszczak K. Lewandowska Jacek Tabor Bartosz Zieliñski 34 98 0 06 Dec 2021
Towards A Rigorous Science of Interpretable Machine Learning Finale Doshi-Velez Been Kim XAI FaML 251 3,683 0 28 Feb 2017
Densely Connected Convolutional Networks Gao Huang Zhuang Liu L. V. D. van der Maaten Kilian Q. Weinberger PINN 3DV 258 36,371 0 25 Aug 2016
ImageNet Large Scale Visual Recognition Challenge Olga Russakovsky Jia Deng Hao Su J. Krause S. Satheesh ... A. Karpathy A. Khosla Michael S. Bernstein Alexander C. Berg Li Fei-Fei VLM ObjD 296 39,198 0 01 Sep 2014