Interpreting Graph Neural Networks for NLP With Differentiable Edge Masking

1 October 2020

Papers citing "Interpreting Graph Neural Networks for NLP With Differentiable Edge Masking"

32 / 32 papers shown

Title
Framework GNN-AID: Graph Neural Network Analysis Interpretation and Defense Kirill Lukyanov Mikhail Drobyshevskiy Georgii Sazonov Mikhail Soloviov Ilya Makarov GNN 41 0 0 06 May 2025
Robustness questions the interpretability of graph neural networks: what to do? Kirill Lukyanov Georgii Sazonov Serafim Boyarsky Ilya Makarov AAML 117 0 0 05 May 2025
Interpretability of Graph Neural Networks to Assess Effects of Global Change Drivers on Ecological Networks Emré Anakok Pierre Barbillon Colin Fontaine Elisa Thébault 47 0 0 19 Mar 2025
Recent Advances in Malware Detection: Graph Learning and Explainability Hossein Shokouhinejad Roozbeh Razavi-Far Hesamodin Mohammadian Mahdi Rabbani Samuel Ansong Griffin Higgins Ali Ghorbani AAML 68 2 0 14 Feb 2025
CROPS: A Deployable Crop Management System Over All Possible State Availabilities Jing Wu Zhixin Lai Shengjie Liu Suiyao Chen Ran Tao Pan Zhao Chuyuan Tao Yikun Cheng N. Hovakimyan OffRL 35 0 0 09 Nov 2024
Explainable Graph Neural Networks Under Fire Zhong Li Simon Geisler Yuhang Wang Stephan Günnemann M. Leeuwen AAML 36 0 0 10 Jun 2024
Towards Fine-Grained Explainability for Heterogeneous Graph Neural Network Tong Li Jiale Deng Yanyan Shen Luyu Qiu Hu Yongxiang Caleb Chen Cao 23 5 0 23 Dec 2023
Self-Explainable Graph Neural Networks for Link Prediction Huaisheng Zhu Dongsheng Luo Xianfeng Tang Junjie Xu Hui Liu Suhang Wang 11 1 0 21 May 2023
Unstructured and structured data: Can we have the best of both worlds with large language models? W. Tan 11 1 0 25 Apr 2023
Combining Stochastic Explainers and Subgraph Neural Networks can Increase Expressivity and Interpretability Indro Spinelli Michele Guerra F. Bianchi Simone Scardapane 25 0 0 14 Apr 2023
Illuminati: Towards Explaining Graph Neural Networks for Cybersecurity Analysis Haoyu He Yuede Ji H. H. Huang 20 20 0 26 Mar 2023
xEM: Explainable Entity Matching in Customer 360 Sukriti Jaitly Deepa Mariam George Balaji Ganesan Muhammad Ameen Srinivas Pusapati 16 0 0 01 Dec 2022
Clenshaw Graph Neural Networks Y. Guo Zhewei Wei GNN 53 10 0 29 Oct 2022
L2XGNN: Learning to Explain Graph Neural Networks G. Serra Mathias Niepert 31 7 0 28 Sep 2022
Evaluating Explainability for Graph Neural Networks Chirag Agarwal Owen Queen Himabindu Lakkaraju Marinka Zitnik 36 99 0 19 Aug 2022
Data Science and Machine Learning in Education G. Benelli Thomas Y. Chen Javier Mauricio Duarte Matthew Feickert Matthew Graham ... K. Terao S. Thais A. Roy J. Vlimant G. Chachamis AI4CE 26 5 0 19 Jul 2022
Trustworthy Graph Neural Networks: Aspects, Methods and Trends He Zhang Bang Wu Xingliang Yuan Shirui Pan Hanghang Tong Jian Pei 41 104 0 16 May 2022
OrphicX: A Causality-Inspired Latent Variable Model for Interpreting Graph Neural Networks Wanyu Lin Hao Lan Hao Wang Baochun Li BDL CML 23 50 0 29 Mar 2022
Explainability in Graph Neural Networks: An Experimental Survey Peibo Li Yixing Yang M. Pagnucco Yang Song 18 31 0 17 Mar 2022
What Has Been Enhanced in my Knowledge-Enhanced Language Model? Yifan Hou Guoji Fu Mrinmaya Sachan KELM 33 1 0 02 Feb 2022
Interpretable and Generalizable Graph Learning via Stochastic Attention Mechanism Siqi Miao Miaoyuan Liu Pan Li 14 196 0 31 Jan 2022
Deconfounding to Explanation Evaluation in Graph Neural Networks Yingmin Wu Xiang Wang An Zhang Xia Hu Fuli Feng Xiangnan He Tat-Seng Chua FAtt CML 12 14 0 21 Jan 2022
Improving Subgraph Recognition with Variational Graph Information Bottleneck Junchi Yu Jie Cao Ran He 22 53 0 18 Dec 2021
Sparse Interventions in Language Models with Differentiable Masking Nicola De Cao Leon Schmid Dieuwke Hupkes Ivan Titov 25 27 0 13 Dec 2021
Interpreting Deep Learning Models in Natural Language Processing: A Review Xiaofei Sun Diyi Yang Xiaoya Li Tianwei Zhang Yuxian Meng Han Qiu Guoyin Wang Eduard H. Hovy Jiwei Li 17 44 0 20 Oct 2021
A Review of the Gumbel-max Trick and its Extensions for Discrete Stochasticity in Machine Learning Iris A. M. Huijben W. Kool Max B. Paulus Ruud J. G. van Sloun 24 92 0 04 Oct 2021
BrainNNExplainer: An Interpretable Graph Neural Network Framework for Brain Network based Disease Analysis Hejie Cui Wei Dai Yanqiao Zhu Xiaoxiao Li Lifang He Carl Yang 18 27 0 11 Jul 2021
A Survey on Graph-Based Deep Learning for Computational Histopathology David Ahmedt-Aristizabal M. Armin Simon Denman Clinton Fookes L. Petersson GNN AI4CE 13 105 0 01 Jul 2021
Reimagining GNN Explanations with ideas from Tabular Data Anjali Singh K. ShamanthRNayak Balaji Ganesan LMTD 20 1 0 23 Jun 2021
Probing GNN Explainers: A Rigorous Theoretical and Empirical Analysis of GNN Explanation Methods Chirag Agarwal Marinka Zitnik Himabindu Lakkaraju 16 51 0 16 Jun 2021
Improving fairness in machine learning systems: What do industry practitioners need? Kenneth Holstein Jennifer Wortman Vaughan Hal Daumé Miroslav Dudík Hanna M. Wallach FaML HAI 192 742 0 13 Dec 2018
Interpretable Graph Convolutional Neural Networks for Inference on Noisy Knowledge Graphs Daniel Neil Joss Briody A. Lacoste Aaron Sim Páidí Creed Amir Saffari GNN 66 35 0 01 Dec 2018