Towards Robust Explanations for Deep Neural Networks

Towards Robust Explanations for Deep Neural Networks

18 December 2020

Ann-Kathrin Dombrowski

Christopher J. Anders

Papers citing "Towards Robust Explanations for Deep Neural Networks"

19 / 19 papers shown

Title
Navigating the Maze of Explainable AI: A Systematic Approach to Evaluating Methods and Metrics Lukas Klein Carsten T. Lüth U. Schlegel Till J. Bungert Mennatallah El-Assady Paul F. Jäger XAI ELM 42 2 0 03 Jan 2025
MambaLRP: Explaining Selective State Space Sequence Models F. Jafari G. Montavon Klaus-Robert Müller Oliver Eberle Mamba 59 9 0 11 Jun 2024
Robust Ranking Explanations Chao Chen Chenghua Guo Guixiang Ma Ming Zeng Xi Zhang Sihong Xie FAtt AAML 35 0 0 08 Jul 2023
Overcoming Adversarial Attacks for Human-in-the-Loop Applications Ryan McCoppin Marla Kennedy P. Lukyanenko Sean M. Kennedy AAML 18 1 0 09 Jun 2023
Disentangled Explanations of Neural Network Predictions by Finding Relevant Subspaces Pattarawat Chormai J. Herrmann Klaus-Robert Muller G. Montavon FAtt 45 17 0 30 Dec 2022
Robust Explanation Constraints for Neural Networks Matthew Wicker Juyeon Heo Luca Costabello Adrian Weller FAtt 21 17 0 16 Dec 2022
Towards More Robust Interpretation via Local Gradient Alignment Sunghwan Joo Seokhyeon Jeong Juyeon Heo Adrian Weller Taesup Moon FAtt 25 5 0 29 Nov 2022
What Makes a Good Explanation?: A Harmonized View of Properties of Explanations Zixi Chen Varshini Subhash Marton Havasi Weiwei Pan Finale Doshi-Velez XAI FAtt 33 18 0 10 Nov 2022
On the Robustness of Explanations of Deep Neural Network Models: A Survey Amlan Jyoti Karthik Balaji Ganesh Manoj Gayala Nandita Lakshmi Tunuguntla Sandesh Kamath V. Balasubramanian XAI FAtt AAML 32 4 0 09 Nov 2022
Efficiently Training Low-Curvature Neural Networks Suraj Srinivas Kyle Matoba Himabindu Lakkaraju F. Fleuret AAML 23 15 0 14 Jun 2022
Investigating the fidelity of explainable artificial intelligence methods for applications of convolutional neural networks in geoscience Antonios Mamalakis E. Barnes I. Ebert‐Uphoff 19 73 0 07 Feb 2022
Debiased-CAM to mitigate systematic error with faithful visual explanations of machine learning Wencan Zhang Mariella Dimiccoli Brian Y. Lim FAtt 19 1 0 30 Jan 2022
A Survey on the Robustness of Feature Importance and Counterfactual Explanations Saumitra Mishra Sanghamitra Dutta Jason Long Daniele Magazzeni AAML 9 58 0 30 Oct 2021
Self-learn to Explain Siamese Networks Robustly Chao Chen Yifan Shen Guixiang Ma Xiangnan Kong S. Rangarajan Xi Zhang Sihong Xie 38 5 0 15 Sep 2021
Explaining Bayesian Neural Networks Kirill Bykov Marina M.-C. Höhne Adelaida Creosteanu Klaus-Robert Muller Frederick Klauschen Shinichi Nakajima Marius Kloft BDL AAML 31 25 0 23 Aug 2021
Neural Network Attribution Methods for Problems in Geoscience: A Novel Synthetic Benchmark Dataset Antonios Mamalakis I. Ebert‐Uphoff E. Barnes OOD 23 75 0 18 Mar 2021
Visual explanation of black-box model: Similarity Difference and Uniqueness (SIDU) method Satya M. Muddamsetty M. N. Jahromi Andreea-Emilia Ciontos Laura M. Fenoy T. Moeslund AAML 32 26 0 26 Jan 2021
Debiased-CAM to mitigate image perturbations with faithful visual explanations of machine learning Wencan Zhang Mariella Dimiccoli Brian Y. Lim FAtt 21 18 0 10 Dec 2020
Methods for Interpreting and Understanding Deep Neural Networks G. Montavon Wojciech Samek K. Müller FaML 234 2,238 0 24 Jun 2017