Gavneet Singh Chadha

According to our database, Gavneet Singh Chadha authored at least 18 papers between 2017 and 2023.

Collaborative distances:

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

2023

Gradient Monitored Reinforcement Learning.

Mohammed Sharafath Abdul Hameed, Gavneet Singh Chadha, Andreas Schwung, Steven X. Ding

IEEE Trans. Neural Networks Learn. Syst., August, 2023

2022

Contrastive learning based self-supervised time-series analysis.

Johannes Pöppelbaum, Gavneet Singh Chadha, Andreas Schwung

Appl. Soft Comput., 2022

Shared Temporal Attention Transformer for Remaining Useful Lifetime Estimation.

Gavneet Singh Chadha, Sayed Rafay Bin Shah, Andreas Schwung, Steven X. Ding

IEEE Access, 2022

2021

Deep Convolutional Clustering-Based Time Series Anomaly Detection.

Gavneet Singh Chadha, Intekhab Islam, Andreas Schwung, Steven X. Ding

Sensors, 2021

A Sequence-to-Sequence Approach for Remaining Useful Lifetime Estimation Using Attention-augmented Bidirectional LSTM.

Sayed Rafay Bin Shah, Gavneet Singh Chadha, Andreas Schwung, Steven X. Ding

Intell. Syst. Appl., 2021

Generalized dilation convolutional neural networks for remaining useful lifetime estimation.

Gavneet Singh Chadha, Utkarsh Panara, Andreas Schwung, Steven X. Ding

Neurocomputing, 2021

Generalized Dilation Structures in Convolutional Neural Networks.

Gavneet Singh Chadha, Jan Niclas Reimann, Andreas Schwung

Proceedings of the 10th International Conference on Pattern Recognition Applications and Methods, 2021

2020

Permutation Learning in Convolutional Neural Networks for Time-Series Analysis.

Gavneet Singh Chadha, Jinwoo Kim, Andreas Schwung, Steven X. Ding

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2020, 2020

Remaining Useful Lifetime Estimation with Sobolev Training.

Gavneet Singh Chadha, S. M. Nazmus Sakeib, Andreas Schwung

Proceedings of the 25th IEEE International Conference on Emerging Technologies and Factory Automation, 2020

2019

Learning the Non-linearity in Convolutional Neural Networks.

Gavneet Singh Chadha, Andreas Schwung

CoRR, 2019

Generalized Dilation Neural Networks.

Gavneet Singh Chadha, Jan Niclas Reimann, Andreas Schwung

CoRR, 2019

Traffic Sign Detection Using R-CNN.

Philipp Rehlaender, Maik Schroeer, Gavneet Singh Chadha, Andreas Schwung

Proceedings of the Recent Advances in Big Data and Deep Learning, 2019

Regularizing Neural Networks with Gradient Monitoring.

Gavneet Singh Chadha, Elnaz Meydani, Andreas Schwung

Proceedings of the Recent Advances in Big Data and Deep Learning, 2019

Comparison of Semi-supervised Deep Neural Networks for Anomaly Detection in Industrial Processes.

Gavneet Singh Chadha, Arfyan Rabbani, Andreas Schwung

Proceedings of the 17th IEEE International Conference on Industrial Informatics, 2019

Time Series based Fault Detection in Industrial Processes using Convolutional Neural Networks.

Gavneet Singh Chadha, Monica Krishnamoorthy, Andreas Schwung

Proceedings of the IECON 2019, 2019

2018

Integrated IPC for data-driven fault detection.

Fabian Westbrink, Gavneet Singh Chadha, Andreas Schwung

Proceedings of the IEEE Industrial Cyber-Physical Systems, 2018

Optimal dosing of bulk material using mass-flow estimation and DEM simulation.

Gavneet Singh Chadha, Fabian Westbrink, Thomas Schütte, Andreas Schwung

Proceedings of the IEEE International Conference on Industrial Technology, 2018

2017

Comparison of deep neural network architectures for fault detection in Tennessee Eastman process.

Gavneet Singh Chadha, Andreas Schwung

Proceedings of the 22nd IEEE International Conference on Emerging Technologies and Factory Automation, 2017