Mehmet Orcun Yalcin - Google Scholar

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Mehmet Orcun Yalcin

Mehmet Orcun Yalcin

Maastricht University

Verified email at maastrichtuniversity.nl

Explainable AI Machine Learning Artificial Intelligence


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Viewpoint diversity in search results T Draws, N Roy, O Inel, A Rieger, R Hada, MO Yalcin, B Timmermans, ... European Conference on Information Retrieval, 279-297, 2023	26	2023
An initial study of machine learning underspecification using feature attribution explainable ai algorithms: A covid-19 virus transmission case study J Hinns, X Fan, S Liu, V Raghava Reddy Kovvuri, MO Yalcin, ... PRICAI 2021: Trends in Artificial Intelligence: 18th Pacific Rim …, 2021	11	2021
An investigation of the impact of covid-19 non-pharmaceutical interventions and economic support policies on foreign exchange markets with explainable AI techniques S Liu, MO Yalcin, H Fu, X Fan arXiv preprint arXiv:2111.14620, 2021	5	2021
‘On evaluating correctness of explainable AI algorithms: An empirical study on local explanations for classification MO Yalcin, X Fan 0-7, 2021	4	2021
Beyond Pointfication: A Study on Gamified Mobile Health Apps MO Yalcin, O Yalcin, S Liu	3	2021
Quantifying Underspecification in Machine Learning with Explainable AI J Hinns
Evaluating Feature Attribution Explainable AI Methods on Nonmonotonic Datasets Generated with Abstract Argumentation MO Yalcin, X Fan
On Evaluating Feature Attribution Algorithms with Propositional Logic MO Yalcin, X Fan

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Articles 1–8