6 citations · 19 across the 7 of their papers we have counts for
9 papers
Goal-Oriented Next Best Activity Recommendation using Reinforcement Learning
Prerna Agarwal, Avani Gupta, Renuka Sindhgatta +1
Recommending a sequence of activities for an ongoing case requires that the recommendations conform to the underlying business process and meet the performance goal of either compl…
Explainable AI Enabled Inspection of Business Process Prediction Models
Chun Ouyang, Renuka Sindhgatta, Catarina Moreira
Modern data analytics underpinned by machine learning techniques has become a key enabler to the automation of data-led decision making. As an important branch of state-of-the-art…
Developing a Fidelity Evaluation Approach for Interpretable Machine Learning
Mythreyi Velmurugan, Chun Ouyang, Catarina Moreira +1
Although modern machine learning and deep learning methods allow for complex and in-depth data analytics, the predictive models generated by these methods are often highly complex,…
Evaluating Explainable Methods for Predictive Process Analytics: A Functionally-Grounded Approach
Mythreyi Velmurugan, Chun Ouyang, Catarina Moreira +1
Predictive process analytics focuses on predicting the future states of running instances of a business process. While advanced machine learning techniques have been used to increa…
An Interpretable Probabilistic Approach for Demystifying Black-box Predictive Models
Catarina Moreira, Yu-Liang Chou, Mythreyi Velmurugan +3
The use of sophisticated machine learning models for critical decision making is faced with a challenge that these models are often applied as a "black-box". This has led to an inc…
An Investigation of Interpretability Techniques for Deep Learning in Predictive Process Analytics
Catarina Moreira, Renuka Sindhgatta, Chun Ouyang +2
This paper explores interpretability techniques for two of the most successful learning algorithms in medical decision-making literature: deep neural networks and random forests. W…