47 citations · 77 across the 14 of their papers we have counts for
5 papers · 1 filter
AutoMixer for Improved Multivariate Time-Series Forecasting on Business and IT Observability Data
Santosh Palaskar, Vijay Ekambaram, Arindam Jati +11
The efficiency of business processes relies on business key performance indicators (Biz-KPIs), that can be negatively impacted by IT failures. Business and IT Observability (BizITO…
Building Interpretable Models for Business Process Prediction using Shared and Specialised Attention Mechanisms
Bemali Wickramanayake, Zhipeng He, Chun Ouyang +3
In this paper, we address the "black-box" problem in predictive process analytics by building interpretable models that are capable to inform both what and why is a prediction. Pre…
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,…
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…
Exploring Interpretability for Predictive Process Analytics
Renuka Sindhgatta, Chun Ouyang, Catarina Moreira
Modern predictive analytics underpinned by machine learning techniques has become a key enabler to the automation of data-driven decision making. In the context of business process…