Alaaeddine Chaoub
YOU?
Author Swipe
View article: Deep learning representations for prognostics and health management
Deep learning representations for prognostics and health management Open
This thesis contributes to the application of Deep Learning (DL) in Remaining useful life (RUL) prediction of industrial equipment, addressing significant challenges in this field. Our research is driven by the need to develop DL architect…
View article: Towards interpreting deep learning models for industry 4.0 with gated mixture of experts
Towards interpreting deep learning models for industry 4.0 with gated mixture of experts Open
International audience
View article: Deep Learning Representation Pre-training for Industry 4.0
Deep Learning Representation Pre-training for Industry 4.0 Open
Deep learning (DL) approaches have multiple potential advantages that have been explored in various fields, but for prognostic and health management (PHM) applications, this is not the case due to the lack of data in particular application…
View article: Learning Representations with End-to-End Models for Improved Remaining Useful Life Prognostic
Learning Representations with End-to-End Models for Improved Remaining Useful Life Prognostic Open
Remaining Useful Life (RUL) of equipment is defined as the duration between the current time and its failure. An accurate and reliable prognostic of the remaining useful life provides decision-makers with valuable information to adopt an a…
View article: Learning representations with end-to-end models for improved remaining useful life prognostic
Learning representations with end-to-end models for improved remaining useful life prognostic Open
International audience
View article: Learning representations with end-to-end models for improved remaining useful life prognostics
Learning representations with end-to-end models for improved remaining useful life prognostics Open
The remaining Useful Life (RUL) of equipment is defined as the duration between the current time and its failure. An accurate and reliable prognostic of the remaining useful life provides decision-makers with valuable information to adopt …
View article: Learning representations with end-to-end models for improved remaining\n useful life prognostics
Learning representations with end-to-end models for improved remaining\n useful life prognostics Open
The remaining Useful Life (RUL) of equipment is defined as the duration\nbetween the current time and its failure. An accurate and reliable prognostic\nof the remaining useful life provides decision-makers with valuable information\nto ado…