82 citations · 150 across the 20 of their papers we have counts for
6 papers · 1 filter
From Data to Decision: A Multi-Stage Framework for Class Imbalance Mitigation in Optical Network Failure Analysis
Yousuf Moiz Ali, Jaroslaw E. Prilepsky, Nicola Sambo +5
Machine learning-based failure management in optical networks has gained significant attention in recent years. However, severe class imbalance, where normal instances vastly outnu…
Dual Path Learning -- learning from noise and context for medical image denoising
Jitindra Fartiyal, Pedro Freire, Yasmeen Whayeb +3
Medical imaging plays a critical role in modern healthcare, enabling clinicians to accurately diagnose diseases and develop effective treatment plans. However, noise, often introdu…
Pre-, In-, and Post-Processing Class Imbalance Mitigation Techniques for Failure Detection in Optical Networks
Yousuf Moiz Ali, Jaroslaw E. Prilepsky, Nicola Sambo +5
We compare pre-, in-, and post-processing techniques for class imbalance mitigation in optical network failure detection. Threshold Adjustment achieves the highest F1 gain (15.3%),…
Reverse energy flows: the physical mechanism underling dramatic reduction of loss in hollow-core fibers
Andrey Pryamikov, Sergei Turitsyn
Hollow-core fibers (HCFs) with claddings composed of silica glass capillaries have recently attracted a great deal of attention following the demonstration of optical loss levels l…
Roadmap on Neuromorphic Photonics
Daniel Brunner, Bhavin J. Shastri, Mohammed A. Al Qadasi +147
This roadmap consolidates recent advances while exploring emerging applications, reflecting the remarkable diversity of hardware platforms, neuromorphic concepts, and implementatio…
Optical neuromorphic computing via temporal up-sampling and trainable encoding on a telecom device platform
Egor Manuylovich, Dmitrii Stoliarov, David Saad +1
Mapping input signals to a high-dimensional space is a critical concept in various neuromorphic computing paradigms, including models such as Reservoir Computing (RC) and Extreme L…