Towards Better Understanding Attribution Methods

Towards Better Understanding Attribution Methods

20 May 2022

Bernt Schiele

Papers citing "Towards Better Understanding Attribution Methods"

8 / 8 papers shown

Title
B-cosification: Transforming Deep Neural Networks to be Inherently Interpretable Shreyash Arya Sukrut Rao Moritz Bohle Bernt Schiele 81 2 0 28 Jan 2025
What Sketch Explainability Really Means for Downstream Tasks Hmrishav Bandyopadhyay Pinaki Nath Chowdhury A. Bhunia Aneeshan Sain Tao Xiang Yi-Zhe Song 30 4 0 14 Mar 2024
FunnyBirds: A Synthetic Vision Dataset for a Part-Based Analysis of Explainable AI Methods Robin Hesse Simone Schaub-Meyer Stefan Roth AAML 37 33 0 11 Aug 2023
Neural Insights for Digital Marketing Content Design F. Kong Yuan Li Houssam Nassif Tanner Fiez Ricardo Henao Shreya Chakrabarti 3DV 27 10 0 02 Feb 2023
SpArX: Sparse Argumentative Explanations for Neural Networks [Technical Report] Hamed Ayoobi Nico Potyka Francesca Toni 24 18 0 23 Jan 2023
Opti-CAM: Optimizing saliency maps for interpretability Hanwei Zhang Felipe Torres R. Sicre Yannis Avrithis Stéphane Ayache 41 22 0 17 Jan 2023
Evaluating Feature Attribution Methods for Electrocardiogram J. Suh Jimyeong Kim Euna Jung Wonjong Rhee FAtt 22 2 0 23 Nov 2022
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 307 39,238 0 01 Sep 2014