Abstract Machine Learning (ML) has been enjoying an unprecedented surge in applications
that solve problems and enable automation in diverse domains. Primarily, this is due to the …

Machine learning (ML) has disrupted a wide range of science and engineering disciplines in
recent years. ML applications in optical communications and networking are also gaining …

With the rapid development of Internet and communication systems, both in the aspect of
services and technologies, communication networks have been suffering increasing …

Self-tuning optical systems are of growing importance in technological applications such as
mode-locked fiber lasers. Such self-tuning paradigms require intelligent algorithms capable …

Failure management plays a role of capital importance in optical networks to avoid service
disruptions and to satisfy customers' service level agreements. Machine learning (ML) …

To support the development of intelligent optical networks, accurate modeling of the physical
layer is crucial. Digital twin (DT) modeling, which relies on continuous learning with real-time …

Machine learning is widely used to solve networking challenges, ranging from traffic
classification and anomaly detection to network configuration. However, machine learning …

Time series prediction problems are a difficult type of predictive modeling problem. In this
paper, we propose a time series prediction method based on a variant long short-term …

Failure management plays a significant role in optical networks. It ensures secure operation,
mitigates potential risks, and executes proactive protection. Machine learning (ML) is …

This white paper on AI/ML as enablers of 5G and B5G networks is based on contributions
from 5G PPP projects that research, implement and validate 5G and B5G network systems …