Input-Cell Attention Reduces Vanishing Saliency of Recurrent Neural Networks

27 October 2019

Papers citing "Input-Cell Attention Reduces Vanishing Saliency of Recurrent Neural Networks"

7 / 7 papers shown

Title
Explainable AI needs formal notions of explanation correctness Stefan Haufe Rick Wilming Benedict Clark Rustam Zhumagambetov Danny Panknin Ahcène Boubekki XAI 31 1 0 22 Sep 2024
SCAAT: Improving Neural Network Interpretability via Saliency Constrained Adaptive Adversarial Training Rui Xu Wenkang Qin Peixiang Huang Hao Wang Lin Luo FAtt AAML 28 2 0 09 Nov 2023
Data-Centric Debugging: mitigating model failures via targeted data collection Sahil Singla Atoosa Malemir Chegini Mazda Moayeri Soheil Feiz 21 4 0 17 Nov 2022
BolT: Fused Window Transformers for fMRI Time Series Analysis H. Bedel Irmak Sivgin Onat Dalmaz S. Dar Tolga Çukur 59 54 0 23 May 2022
Improving Deep Learning Interpretability by Saliency Guided Training Aya Abdelsalam Ismail H. C. Bravo S. Feizi FAtt 20 79 0 29 Nov 2021
TimeSHAP: Explaining Recurrent Models through Sequence Perturbations João Bento Pedro Saleiro André F. Cruz Mário A. T. Figueiredo P. Bizarro FAtt AI4TS 16 88 0 30 Nov 2020
Methods for Interpreting and Understanding Deep Neural Networks G. Montavon Wojciech Samek K. Müller FaML 234 2,238 0 24 Jun 2017