1 citations · 1 across the 1 of their papers we have counts for
4 papers
Entropy Guided Dynamic Patch Segmentation for Time Series Transformers
Sachith Abeywickrama, Emadeldeen Eldele, Min Wu +2
Patch-based transformers have emerged as efficient and improved long-horizon modeling architectures for time series modeling. Yet, existing approaches rely on temporally-agnostic p…
Physics-Informed Neural Networks in Electromagnetic and Nanophotonic Design
Omar A. M. Abdelraouf, Abdulrahman M. A. Ahmed, Emadeldeen Eldele +1
The fusion of artificial intelligence (AI) with physics-guided frameworks has opened transformative avenues for advancing the design and optimization of electromagnetic and nanopho…
Bridging Distribution Gaps in Time Series Foundation Model Pretraining with Prototype-Guided Normalization
Peiliang Gong, Emadeldeen Eldele, Min Wu +3
Foundation models have achieved remarkable success across diverse machine-learning domains through large-scale pretraining on large, diverse datasets. However, pretraining on such…
UniFault: A Fault Diagnosis Foundation Model from Bearing Data
Emadeldeen Eldele, Mohamed Ragab, Xu Qing +5
Machine fault diagnosis (FD) is a critical task for predictive maintenance, enabling early fault detection and preventing unexpected failures. Despite its importance, existing FD m…