A Rate-Distortion Framework for Explaining Neural Network Decisions

A Rate-Distortion Framework for Explaining Neural Network Decisions

27 May 2019

Papers citing "A Rate-Distortion Framework for Explaining Neural Network Decisions"

12 / 12 papers shown

Title
Prototypical Self-Explainable Models Without Re-training Srishti Gautam Ahcène Boubekki Marina M.-C. Höhne Michael C. Kampffmeyer 34 2 0 13 Dec 2023
On Interpretable Approaches to Cluster, Classify and Represent Multi-Subspace Data via Minimum Lossy Coding Length based on Rate-Distortion Theory Kaige Lu Avraham Chapman 45 0 0 21 Feb 2023
Explaining Image Classifiers with Multiscale Directional Image Representation Stefan Kolek Robert Windesheim Héctor Andrade-Loarca Gitta Kutyniok Ron Levie 29 4 0 22 Nov 2022
New Definitions and Evaluations for Saliency Methods: Staying Intrinsic, Complete and Sound Arushi Gupta Nikunj Saunshi Dingli Yu Kaifeng Lyu Sanjeev Arora AAML FAtt XAI 31 5 0 05 Nov 2022
Learning Fair Representations via Rate-Distortion Maximization Somnath Basu Roy Chowdhury Snigdha Chaturvedi FaML 8 14 0 31 Jan 2022
Interpretable Neural Networks with Frank-Wolfe: Sparse Relevance Maps and Relevance Orderings Jan Macdonald Mathieu Besançon Sebastian Pokutta 32 11 0 15 Oct 2021
A Rate-Distortion Framework for Explaining Black-box Model Decisions Stefan Kolek Duc Anh Nguyen Ron Levie Joan Bruna Gitta Kutyniok 35 15 0 12 Oct 2021
Cartoon Explanations of Image Classifiers Stefan Kolek Duc Anh Nguyen Ron Levie Joan Bruna Gitta Kutyniok FAtt 38 15 0 07 Oct 2021
This looks more like that: Enhancing Self-Explaining Models by Prototypical Relevance Propagation Srishti Gautam Marina M.-C. Höhne Stine Hansen Robert Jenssen Michael C. Kampffmeyer 27 49 0 27 Aug 2021
Learning Diverse and Discriminative Representations via the Principle of Maximal Coding Rate Reduction Yaodong Yu Kwan Ho Ryan Chan Chong You Chaobing Song Yi Ma SSL 36 190 0 15 Jun 2020
Explaining Deep Neural Networks and Beyond: A Review of Methods and Applications Wojciech Samek G. Montavon Sebastian Lapuschkin Christopher J. Anders K. Müller XAI 51 82 0 17 Mar 2020
Methods for Interpreting and Understanding Deep Neural Networks G. Montavon Wojciech Samek K. Müller FaML 234 2,238 0 24 Jun 2017