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1808.00033
Cited By
Techniques for Interpretable Machine Learning
31 July 2018
Mengnan Du
Ninghao Liu
Xia Hu
FaML
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Papers citing
"Techniques for Interpretable Machine Learning"
50 / 93 papers shown
Title
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Tehseen Zia
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A Review of Graph-Powered Data Quality Applications for IoT Monitoring Sensor Networks
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Jose M. Barcelo-Ordinas
J. García-Vidal
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Fair MP-BOOST: Fair and Interpretable Minipatch Boosting
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Genevera I. Allen
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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
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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
18
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
39
3
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08 Jan 2024
Improving Interpretation Faithfulness for Vision Transformers
Lijie Hu
Yixin Liu
Ninghao Liu
Mengdi Huai
Lichao Sun
Di Wang
32
5
0
29 Nov 2023
Concept Distillation: Leveraging Human-Centered Explanations for Model Improvement
Avani Gupta
Saurabh Saini
P. J. Narayanan
25
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26 Nov 2023
Identifying DNA Sequence Motifs Using Deep Learning
Asmita Poddar
Vladimir Uzun
Elizabeth Tunbridge
W. Haerty
A. Nevado-Holgado
18
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0
20 Nov 2023
When to Trust AI: Advances and Challenges for Certification of Neural Networks
M. Kwiatkowska
Xiyue Zhang
AAML
25
8
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20 Sep 2023
Modeling Inverse Demand Function with Explainable Dual Neural Networks
Zhiyu Cao
Zihan Chen
P. Mishra
Hamed Amini
Zachary Feinstein
25
2
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26 Jul 2023
Prediction of Handball Matches with Statistically Enhanced Learning via Estimated Team Strengths
Florian Felice
Christophe Ley
18
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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
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DEGREE: Decomposition Based Explanation For Graph Neural Networks
Qizhang Feng
Ninghao Liu
Fan Yang
Ruixiang Tang
Mengnan Du
Xia Hu
23
22
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22 May 2023
A System's Approach Taxonomy for User-Centred XAI: A Survey
Ehsan Emamirad
Pouya Ghiasnezhad Omran
A. Haller
S. Gregor
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1
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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
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05 Mar 2023
A Scalable Space-efficient In-database Interpretability Framework for Embedding-based Semantic SQL Queries
P. Kudva
R. Bordawekar
Apoorva Nitsure
17
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23 Feb 2023
AutoDOViz: Human-Centered Automation for Decision Optimization
D. Weidele
S. Afzal
Abel N. Valente
Cole Makuch
Owen Cornec
...
Radu Marinescu
Paulito Palmes
Elizabeth M. Daly
Loraine Franke
D. Haehn
OffRL
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Less is More: The Influence of Pruning on the Explainability of CNNs
David Weber
F. Merkle
Pascal Schöttle
Stephan Schlögl
Martin Nocker
FAtt
34
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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
26
160
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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 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
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13 Dec 2022
Graph Learning for Anomaly Analytics: Algorithms, Applications, and Challenges
Jing Ren
Feng Xia
Azadeh Noori Hoshyar
Charu C. Aggarwal
42
26
0
11 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
21
14
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30 Nov 2022
Relative Sparsity for Medical Decision Problems
Samuel J. Weisenthal
Sally W. Thurston
Ashkan Ertefaie
27
2
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29 Nov 2022
Holding AI to Account: Challenges for the Delivery of Trustworthy AI in Healthcare
Rob Procter
P. Tolmie
M. Rouncefield
11
31
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29 Nov 2022
Attribution-based XAI Methods in Computer Vision: A Review
Kumar Abhishek
Deeksha Kamath
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18
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27 Nov 2022
SEAT: Stable and Explainable Attention
Lijie Hu
Yixin Liu
Ninghao Liu
Mengdi Huai
Lichao Sun
Di Wang
OOD
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18
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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
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09 Nov 2022
Explaining Anomalies using Denoising Autoencoders for Financial Tabular Data
Timur Sattarov
Dayananda Herurkar
Jörn Hees
30
8
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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
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A Survey of Neural Trees
Haoling Li
Jie Song
Mengqi Xue
Haofei Zhang
Jingwen Ye
Lechao Cheng
Mingli Song
AI4CE
20
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Differentially Private Counterfactuals via Functional Mechanism
Fan Yang
Qizhang Feng
Kaixiong Zhou
Jiahao Chen
Xia Hu
24
8
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Activation Template Matching Loss for Explainable Face Recognition
Huawei Lin
Haozhe Liu
Qiufu Li
Linlin Shen
CVBM
29
1
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Maieutic Prompting: Logically Consistent Reasoning with Recursive Explanations
Jaehun Jung
Lianhui Qin
Sean Welleck
Faeze Brahman
Chandra Bhagavatula
Ronan Le Bras
Yejin Choi
ReLM
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223
190
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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
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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
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AI4TS
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Mind the gap: Challenges of deep learning approaches to Theory of Mind
Jaan Aru
Aqeel Labash
Oriol Corcoll
Raul Vicente
22
26
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Dynamic Model Tree for Interpretable Data Stream Learning
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Klaus Broelemann
Gjergji Kasneci
17
7
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A Survey on Aspect-Based Sentiment Classification
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Flavius Frasincar
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109
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Interpretable and Generalizable Graph Learning via Stochastic Attention Mechanism
Siqi Miao
Miaoyuan Liu
Pan Li
14
197
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Debiased-CAM to mitigate systematic error with faithful visual explanations of machine learning
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Mariella Dimiccoli
Brian Y. Lim
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Learning Two-Step Hybrid Policy for Graph-Based Interpretable Reinforcement Learning
Tongzhou Mu
Kaixiang Lin
Fei Niu
Govind Thattai
OffRL
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Fighting Money Laundering with Statistics and Machine Learning
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Alexandros Iosifidis
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Improving ECG Classification Interpretability using Saliency Maps
Yola Jones
F. Deligianni
Jeffrey Stephen Dalton
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Self-Interpretable Model with TransformationEquivariant Interpretation
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Xiaoqian Wang
38
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Defense Against Explanation Manipulation
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Ninghao Liu
Fan Yang
Na Zou
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