Divish Rengasamy

According to our database, Divish Rengasamy authored at least 10 papers between 2018 and 2022.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2022

Feature importance in machine learning models: A fuzzy information fusion approach.

Divish Rengasamy, Jimiama Mafeni Mase, Aayush Kumar, Benjamin Rothwell, Mercedes Torres Torres, Morgan R. Alexander, David A. Winkler, Grazziela P. Figueredo

Neurocomputing, 2022

Anomaly Detection for Unmanned Aerial Vehicle Sensor Data Using a Stacked Recurrent Autoencoder Method with Dynamic Thresholding.

Victoria Bell, Divish Rengasamy, Benjamin Rothwell, Grazziela P. Figueredo

CoRR, 2022

EFI: A Toolbox for Feature Importance Fusion and Interpretation in Python.

Aayush Kumar, Jimiama Mafeni Mase, Divish Rengasamy, Benjamin Rothwell, Mercedes Torres Torres, David A. Winkler, Grazziela P. Figueredo

Proceedings of the Machine Learning, Optimization, and Data Science, 2022

2021

Machine learning to determine the main factors affecting creep rates in laser powder bed fusion.

Salomé Sanchez, Divish Rengasamy, Christopher J. Hyde, Grazziela P. Figueredo, Benjamin Rothwell

J. Intell. Manuf., 2021

Mechanistic Interpretation of Machine Learning Inference: A Fuzzy Feature Importance Fusion Approach.

Divish Rengasamy, Jimiama Mafeni Mase, Mercedes Torres Torres, Benjamin Rothwell, David A. Winkler, Grazziela P. Figueredo

CoRR, 2021

2020

Deep Learning with Dynamically Weighted Loss Function for Sensor-Based Prognostics and Health Management.

Divish Rengasamy, Mina Jafari, Benjamin Rothwell, Xin Chen, Grazziela P. Figueredo

Sensors, 2020

Towards a More Reliable Interpretation of Machine Learning Outputs for Safety-Critical Systems using Feature Importance Fusion.

Divish Rengasamy, Benjamin Rothwell, Grazziela Patrocinio Figueredo

CoRR, 2020

Asymmetric Loss Functions for Deep Learning Early Predictions of Remaining Useful Life in Aerospace Gas Turbine Engines.

Divish Rengasamy, Benjamin Rothwell, Grazziela P. Figueredo

Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

2019

An Intelligent Toolkit for Benchmarking Data-Driven Aerospace Prognostics.

Divish Rengasamy, Jimiama M. M. Mase, Benjamin Rothwell, Grazziela P. Figueredo

Proceedings of the 2019 IEEE Intelligent Transportation Systems Conference, 2019

2018

Deep Learning Approaches to Aircraft Maintenance, Repair and Overhaul: A Review.

Divish Rengasamy, Hervé P. Morvan, Grazziela P. Figueredo

Proceedings of the 21st International Conference on Intelligent Transportation Systems, 2018