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Explainable Artificial Intelligence and Machine Learning: A reality
  rooted perspective

Explainable Artificial Intelligence and Machine Learning: A reality rooted perspective

26 January 2020
F. Emmert-Streib
O. Yli-Harja
M. Dehmer
ArXiv (abs)PDFHTML

Papers citing "Explainable Artificial Intelligence and Machine Learning: A reality rooted perspective"

13 / 13 papers shown
On Explaining Proxy Discrimination and Unfairness in Individual Decisions Made by AI Systems
On Explaining Proxy Discrimination and Unfairness in Individual Decisions Made by AI Systems
Belona Sonna
Alban Grastien
141
1
0
30 Sep 2025
A survey and taxonomy of methods interpreting random forest models
A survey and taxonomy of methods interpreting random forest models
Maissae Haddouchi
A. Berrado
399
11
0
17 Jul 2024
Explainable automatic industrial carbon footprint estimation from bank
  transaction classification using natural language processing
Explainable automatic industrial carbon footprint estimation from bank transaction classification using natural language processingIEEE Access (IEEE Access), 2024
Jaime González-González
Silvia García-Méndez
Francisco de Arriba-Pérez
Francisco J. González Castaño
Oscar Barba-Seara
222
12
0
23 May 2024
Enhancing Breast Cancer Diagnosis in Mammography: Evaluation and
  Integration of Convolutional Neural Networks and Explainable AI
Enhancing Breast Cancer Diagnosis in Mammography: Evaluation and Integration of Convolutional Neural Networks and Explainable AI
Maryam Ahmed
Tooba Bibi
Rizwan Ahmed Khan
Sidra Nasir
434
19
0
05 Apr 2024
Beyond Single-Feature Importance with ICECREAM
Beyond Single-Feature Importance with ICECREAMCLEaR (CLEaR), 2023
M.-J. Oesterle
Patrick Blobaum
Atalanti A. Mastakouri
Elke Kirschbaum
CML
339
1
0
19 Jul 2023
An Efficient Ensemble Explainable AI (XAI) Approach for Morphed Face
  Detection
An Efficient Ensemble Explainable AI (XAI) Approach for Morphed Face DetectionPattern Recognition Letters (PR), 2023
Rudresh Dwivedi
Ritesh Kumar
Deepak Chopra
Pranay Kothari
Manjot Singh
CVBMAAML
190
13
0
23 Apr 2023
Quantifying and Explaining Machine Learning Uncertainty in Predictive
  Process Monitoring: An Operations Research Perspective
Quantifying and Explaining Machine Learning Uncertainty in Predictive Process Monitoring: An Operations Research PerspectiveAnnals of Operations Research (Ann. Oper. Res.), 2023
Nijat Mehdiyev
Maxim Majlatow
Peter Fettke
270
32
0
13 Apr 2023
Explainable AI over the Internet of Things (IoT): Overview,
  State-of-the-Art and Future Directions
Explainable AI over the Internet of Things (IoT): Overview, State-of-the-Art and Future DirectionsIEEE Open Journal of the Communications Society (OJ-COMS), 2022
Senthil Kumar Jagatheesaperumal
Quoc-Viet Pham
Rukhsana Ruby
Zhaohui Yang
Chunmei Xu
Zhaoyang Zhang
345
97
0
02 Nov 2022
Enriching Artificial Intelligence Explanations with Knowledge Fragments
Enriching Artificial Intelligence Explanations with Knowledge FragmentsFuture Internet (FI), 2022
Jože M. Rožanec
Elena Trajkova
I. Novalija
Patrik Zajec
K. Kenda
B. Fortuna
Dunja Mladenić
195
10
0
12 Apr 2022
TorchEsegeta: Framework for Interpretability and Explainability of
  Image-based Deep Learning Models
TorchEsegeta: Framework for Interpretability and Explainability of Image-based Deep Learning Models
S. Chatterjee
Arnab Das
Chirag Mandal
Budhaditya Mukhopadhyay
Manish Vipinraj
Aniruddh Shukla
R. Rao
Chompunuch Sarasaen
Oliver Speck
A. Nürnberger
MedIm
234
16
0
16 Oct 2021
Shapley variable importance clouds for interpretable machine learning
Shapley variable importance clouds for interpretable machine learning
Yilin Ning
M. Ong
Bibhas Chakraborty
B. Goldstein
Daniel Ting
Roger Vaughan
Nan Liu
FAtt
182
97
0
06 Oct 2021
Ensuring the Robustness and Reliability of Data-Driven Knowledge
  Discovery Models in Production and Manufacturing
Ensuring the Robustness and Reliability of Data-Driven Knowledge Discovery Models in Production and ManufacturingFrontiers in Artificial Intelligence (FAI), 2020
S. Tripathi
David Muhr
Manuel Brunner
F. Emmert-Streib
H. Jodlbauer
M. Dehmer
175
59
0
28 Jul 2020
Machine Unlearning: Linear Filtration for Logit-based Classifiers
Machine Unlearning: Linear Filtration for Logit-based ClassifiersMachine-mediated learning (ML), 2020
Thomas Baumhauer
Pascal Schöttle
Matthias Zeppelzauer
MU
385
158
0
07 Feb 2020
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