Explaining a black-box using Deep Variational Information Bottleneck
Approach

Explaining a black-box using Deep Variational Information Bottleneck Approach

19 February 2019

Papers citing "Explaining a black-box using Deep Variational Information Bottleneck Approach"

19 / 19 papers shown

Title
DocVXQA: Context-Aware Visual Explanations for Document Question Answering Mohamed Ali Souibgui Changkyu Choi Andrey Barsky Kangsoo Jung Ernest Valveny Dimosthenis Karatzas 28 0 0 12 May 2025
CRFU: Compressive Representation Forgetting Against Privacy Leakage on Machine Unlearning Weiqi Wang Chenhan Zhang Zhiyi Tian Shushu Liu Shui Yu MU 47 0 0 27 Feb 2025
Task-Augmented Cross-View Imputation Network for Partial Multi-View Incomplete Multi-Label Classification Xiaohuan Lu Lian Zhao Wai Keung Wong Jie Wen Jiang Long Wulin Xie 36 1 0 12 Sep 2024
ICST-DNET: An Interpretable Causal Spatio-Temporal Diffusion Network for Traffic Speed Prediction Yi Rong Yingchi Mao Yinqiu Liu Ling Chen Xiaoming He Dusit Niyato DiffM 23 1 0 22 Apr 2024
BELLA: Black box model Explanations by Local Linear Approximations N. Radulovic Albert Bifet Fabian M. Suchanek FAtt 37 1 0 18 May 2023
Posthoc Interpretation via Quantization Francesco Paissan Cem Subakan Mirco Ravanelli MQ 24 6 0 22 Mar 2023
Interpretability with full complexity by constraining feature information Kieran A. Murphy Danielle Bassett FAtt 35 5 0 30 Nov 2022
Revisiting Attention Weights as Explanations from an Information Theoretic Perspective Bingyang Wen K. P. Subbalakshmi Fan Yang FAtt 27 6 0 31 Oct 2022
Explanation-based Counterfactual Retraining(XCR): A Calibration Method for Black-box Models Liu Zhendong Wenyu Jiang Yan Zhang Chongjun Wang CML 11 0 0 22 Jun 2022
Variational Distillation for Multi-View Learning Xudong Tian Zhizhong Zhang Cong Wang Wensheng Zhang Yanyun Qu Lizhuang Ma Zongze Wu Yuan Xie Dacheng Tao 26 5 0 20 Jun 2022
Listen to Interpret: Post-hoc Interpretability for Audio Networks with NMF Jayneel Parekh Sanjeel Parekh Pavlo Mozharovskyi Florence dÁlché-Buc G. Richard 24 22 0 23 Feb 2022
The Out-of-Distribution Problem in Explainability and Search Methods for Feature Importance Explanations Peter Hase Harry Xie Joey Tianyi Zhou OODD LRM FAtt 29 91 0 01 Jun 2021
Progressive Interpretation Synthesis: Interpreting Task Solving by Quantifying Previously Used and Unused Information Zhengqi He Taro Toyoizumi 19 1 0 08 Jan 2021
Inserting Information Bottlenecks for Attribution in Transformers Zhiying Jiang Raphael Tang Ji Xin Jimmy J. Lin 41 6 0 27 Dec 2020
Learning Variational Word Masks to Improve the Interpretability of Neural Text Classifiers Hanjie Chen Yangfeng Ji AAML VLM 15 63 0 01 Oct 2020
Generative causal explanations of black-box classifiers Matthew R. O’Shaughnessy Gregory H. Canal Marissa Connor Mark A. Davenport Christopher Rozell CML 30 73 0 24 Jun 2020
On the Maximum Mutual Information Capacity of Neural Architectures Brandon Foggo Nan Yu TPM 23 3 0 10 Jun 2020
Why Attentions May Not Be Interpretable? Bing Bai Jian Liang Guanhua Zhang Hao Li Kun Bai Fei Wang FAtt 25 56 0 10 Jun 2020
Adversarial Infidelity Learning for Model Interpretation Jian Liang Bing Bai Yuren Cao Kun Bai Fei Wang AAML 54 18 0 09 Jun 2020