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Building Interpretable Models for Business Process Prediction using Shared and Specialised Attention Mechanisms


Sep 03, 2021
Bemali Wickramanayake, Zhipeng He, Chun Ouyang, Catarina Moreira, Yue Xu, Renuka Sindhgatta

* 25 pages, 11 figures, 5 tables 

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Explainable AI Enabled Inspection of Business Process Prediction Models


Jul 16, 2021
Chun Ouyang, Renuka Sindhgatta, Catarina Moreira

* 17 pages, 6 figures, 1 table 

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Developing a Fidelity Evaluation Approach for Interpretable Machine Learning


Jun 16, 2021
Mythreyi Velmurugan, Chun Ouyang, Catarina Moreira, Renuka Sindhgatta


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Evaluating Explainable Methods for Predictive Process Analytics: A Functionally-Grounded Approach


Dec 08, 2020
Mythreyi Velmurugan, Chun Ouyang, Catarina Moreira, Renuka Sindhgatta


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An Interpretable Probabilistic Approach for Demystifying Black-box Predictive Models


Jul 21, 2020
Catarina Moreira, Yu-Liang Chou, Mythreyi Velmurugan, Chun Ouyang, Renuka Sindhgatta, Peter Bruza


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An Investigation of Interpretability Techniques for Deep Learning in Predictive Process Analytics


Feb 21, 2020
Catarina Moreira, Renuka Sindhgatta, Chun Ouyang, Peter Bruza, Andreas Wichert


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Interpreting Predictive Process Monitoring Benchmarks


Dec 22, 2019
Renuka Sindhgatta, Chun Ouyang, Catarina Moreira, Yi Liao

* 16 pages, 9 figures 

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Targeted Example Generation for Compilation Errors


Sep 02, 2019
Umair Z. Ahmed, Renuka Sindhgatta, Nisheeth Srivastava, Amey Karkare

* To appear in 34th IEEE/ACM International Conference on Automated Software Engineering (ASE 2019) 

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Joint Multi-Domain Learning for Automatic Short Answer Grading


Feb 25, 2019
Swarnadeep Saha, Tejas I. Dhamecha, Smit Marvaniya, Peter Foltz, Renuka Sindhgatta, Bikram Sengupta

* 11 pages 

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Memory-Augmented Neural Networks for Predictive Process Analytics


Feb 03, 2018
Asjad Khan, Hung Le, Kien Do, Truyen Tran, Aditya Ghose, Hoa Dam, Renuka Sindhgatta


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