Techniques for Interpretable Machine Learning

31 July 2018

Ninghao Liu

Papers citing "Techniques for Interpretable Machine Learning"

50 / 87 papers shown

Title
Self-Explaining Hypergraph Neural Networks for Diagnosis Prediction Leisheng Yu Yanxiao Cai Minxing Zhang Xia Hu FAtt 144 0 0 15 Feb 2025
Faithful Counterfactual Visual Explanations (FCVE) Bismillah Khan Syed Ali Tariq Tehseen Zia Muhammad Ahsan David Windridge 44 0 0 12 Jan 2025
Towards Counterfactual and Contrastive Explainability and Transparency of DCNN Image Classifiers Syed Ali Tariq Tehseen Zia Mubeen Ghafoor AAML 62 7 0 12 Jan 2025
A Review of Graph-Powered Data Quality Applications for IoT Monitoring Sensor Networks Pau Ferrer-Cid Jose M. Barcelo-Ordinas J. García-Vidal 42 2 0 28 Oct 2024
Fair MP-BOOST: Fair and Interpretable Minipatch Boosting Camille Olivia Little Genevera I. Allen 25 0 0 01 Apr 2024
Explainable AI for Safe and Trustworthy Autonomous Driving: A Systematic Review Anton Kuznietsov Balint Gyevnar Cheng Wang Steven Peters Stefano V. Albrecht XAI 28 26 0 08 Feb 2024
B-Cos Aligned Transformers Learn Human-Interpretable Features Manuel Tran Amal Lahiani Yashin Dicente Cid Melanie Boxberg Peter Lienemann C. Matek S. J. Wagner Fabian J. Theis Eldad Klaiman Tingying Peng MedIm ViT 13 2 0 16 Jan 2024
Explaining the Power of Topological Data Analysis in Graph Machine Learning Funmilola Mary Taiwo Umar Islambekov Cüneyt Gürcan Akçora AI4CE 31 3 0 08 Jan 2024
Improving Interpretation Faithfulness for Vision Transformers Lijie Hu Yixin Liu Ninghao Liu Mengdi Huai Lichao Sun Di Wang 27 5 0 29 Nov 2023
Concept Distillation: Leveraging Human-Centered Explanations for Model Improvement Avani Gupta Saurabh Saini P. J. Narayanan 25 6 0 26 Nov 2023
Identifying DNA Sequence Motifs Using Deep Learning Asmita Poddar Vladimir Uzun Elizabeth Tunbridge W. Haerty A. Nevado-Holgado 16 0 0 20 Nov 2023
When to Trust AI: Advances and Challenges for Certification of Neural Networks M. Kwiatkowska Xiyue Zhang AAML 12 8 0 20 Sep 2023
Modeling Inverse Demand Function with Explainable Dual Neural Networks Zhiyu Cao Zihan Chen P. Mishra Hamed Amini Zachary Feinstein 25 2 0 26 Jul 2023
Prediction of Handball Matches with Statistically Enhanced Learning via Estimated Team Strengths Florian Felice Christophe Ley 13 1 0 20 Jul 2023
A Novel Explainable Artificial Intelligence Model in Image Classification problem Quoc Hung Cao Hung Truong Thanh Nguyen V. Nguyen Xuan Phong Nguyen VLM 19 5 0 09 Jul 2023
DEGREE: Decomposition Based Explanation For Graph Neural Networks Qizhang Feng Ninghao Liu Fan Yang Ruixiang Tang Mengnan Du Xia Hu 23 22 0 22 May 2023
A System's Approach Taxonomy for User-Centred XAI: A Survey Ehsan Emamirad Pouya Ghiasnezhad Omran A. Haller S. Gregor 26 1 0 06 Mar 2023
CoRTX: Contrastive Framework for Real-time Explanation Yu-Neng Chuang Guanchu Wang Fan Yang Quan-Gen Zhou Pushkar Tripathi Xuanting Cai Xia Hu 46 19 0 05 Mar 2023
A Scalable Space-efficient In-database Interpretability Framework for Embedding-based Semantic SQL Queries P. Kudva R. Bordawekar Apoorva Nitsure 12 0 0 23 Feb 2023
Less is More: The Influence of Pruning on the Explainability of CNNs David Weber F. Merkle Pascal Schöttle Stephan Schlögl Martin Nocker FAtt 29 1 0 17 Feb 2023
NeuroExplainer: Fine-Grained Attention Decoding to Uncover Cortical Development Patterns of Preterm Infants Chen Xue Fan Wang Yuanzhuo Zhu Hui Li Deyu Meng Dinggang Shen C. Lian 47 2 0 01 Jan 2023
The State of the Art in Enhancing Trust in Machine Learning Models with the Use of Visualizations Angelos Chatzimparmpas R. Martins I. Jusufi K. Kucher Fabrice Rossi A. Kerren FAtt 24 160 0 22 Dec 2022
Towards Efficient Visual Simplification of Computational Graphs in Deep Neural Networks Rusheng Pan Zhiyong Wang Yating Wei Han Gao Gongchang Ou Caleb Chen Cao Jinglin Xu Tong Xu Wei-Neng Chen GNN 18 4 0 21 Dec 2022
Improving Accuracy Without Losing Interpretability: A ML Approach for Time Series Forecasting Yiqi Sun Zheng Shi Jianshen Zhang Yongzhi Qi Hao Hu Zuo-jun Shen AI4TS 16 0 0 13 Dec 2022
Understanding transit ridership in an equity context through a comparison of statistical and machine learning algorithms Elnaz Yousefzadeh Barri S. Farber H. Jahanshahi Eda Beyazıt 19 14 0 30 Nov 2022
Relative Sparsity for Medical Decision Problems Samuel J. Weisenthal Sally W. Thurston Ashkan Ertefaie 27 2 0 29 Nov 2022
Attribution-based XAI Methods in Computer Vision: A Review Kumar Abhishek Deeksha Kamath 27 18 0 27 Nov 2022
SEAT: Stable and Explainable Attention Lijie Hu Yixin Liu Ninghao Liu Mengdi Huai Lichao Sun Di Wang OOD 24 18 0 23 Nov 2022
DC-Check: A Data-Centric AI checklist to guide the development of reliable machine learning systems Nabeel Seedat F. Imrie M. Schaar 27 12 0 09 Nov 2022
Explaining Anomalies using Denoising Autoencoders for Financial Tabular Data Timur Sattarov Dayananda Herurkar Jörn Hees 30 8 0 21 Sep 2022
Explainable AI for clinical and remote health applications: a survey on tabular and time series data Flavio Di Martino Franca Delmastro AI4TS 28 91 0 14 Sep 2022
A Survey of Neural Trees Haoling Li Jie Song Mengqi Xue Haofei Zhang Jingwen Ye Lechao Cheng Mingli Song AI4CE 15 6 0 07 Sep 2022
Differentially Private Counterfactuals via Functional Mechanism Fan Yang Qizhang Feng Kaixiong Zhou Jiahao Chen Xia Hu 24 8 0 04 Aug 2022
Activation Template Matching Loss for Explainable Face Recognition Huawei Lin Haozhe Liu Qiufu Li Linlin Shen CVBM 27 1 0 05 Jul 2022
Maieutic Prompting: Logically Consistent Reasoning with Recursive Explanations Jaehun Jung Lianhui Qin Sean Welleck Faeze Brahman Chandra Bhagavatula Ronan Le Bras Yejin Choi ReLM LRM 223 190 0 24 May 2022
The Road to Explainability is Paved with Bias: Measuring the Fairness of Explanations Aparna Balagopalan Haoran Zhang Kimia Hamidieh Thomas Hartvigsen Frank Rudzicz Marzyeh Ghassemi 38 77 0 06 May 2022
Robust and Explainable Autoencoders for Unsupervised Time Series Outlier Detection---Extended Version Tung Kieu B. Yang Chenjuan Guo Christian S. Jensen Yan Zhao Feiteng Huang Kai Zheng AI4TS 27 37 0 07 Apr 2022
Mind the gap: Challenges of deep learning approaches to Theory of Mind Jaan Aru Aqeel Labash Oriol Corcoll Raul Vicente 20 26 0 30 Mar 2022
A Survey on Aspect-Based Sentiment Classification Gianni Brauwers Flavius Frasincar LLMAG 31 109 0 27 Mar 2022
Interpretable and Generalizable Graph Learning via Stochastic Attention Mechanism Siqi Miao Miaoyuan Liu Pan Li 14 197 0 31 Jan 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
Learning Two-Step Hybrid Policy for Graph-Based Interpretable Reinforcement Learning Tongzhou Mu Kaixiang Lin Fei Niu Govind Thattai OffRL 22 0 0 21 Jan 2022
Fighting Money Laundering with Statistics and Machine Learning R. Jensen Alexandros Iosifidis 28 13 0 11 Jan 2022
Improving ECG Classification Interpretability using Saliency Maps Yola Jones F. Deligianni Jeffrey Stephen Dalton FAtt 23 19 0 10 Jan 2022
Self-Interpretable Model with TransformationEquivariant Interpretation Yipei Wang Xiaoqian Wang 38 23 0 09 Nov 2021
Defense Against Explanation Manipulation Ruixiang Tang Ninghao Liu Fan Yang Na Zou Xia Hu AAML 39 11 0 08 Nov 2021
Modeling Techniques for Machine Learning Fairness: A Survey Mingyang Wan Daochen Zha Ninghao Liu Na Zou SyDa FaML 30 36 0 04 Nov 2021
Tree-based local explanations of machine learning model predictions, AraucanaXAI Enea Parimbelli G. Nicora Szymon Wilk W. Michalowski Riccardo Bellazzi 16 25 0 15 Oct 2021
LEMON: Explainable Entity Matching Nils Barlaug FAtt AAML 12 9 0 01 Oct 2021
The Impact of Machine Learning on 2D/3D Registration for Image-guided Interventions: A Systematic Review and Perspective Mathias Unberath Cong Gao Yicheng Hu Max Judish Russell H. Taylor Mehran Armand Robert Grupp 21 66 0 04 Aug 2021