Non-technological barriers: the last frontier towards AI-powered intelligent optical networks
FN Khan - Nature Communications, 2024 - nature.com
Abstract Machine learning (ML) has been remarkably successful in transforming numerous
scientific and technological fields in recent years including computer vision, natural …
scientific and technological fields in recent years including computer vision, natural …
Optimizing connectivity: a novel AI approach to assess transmission levels in optical networks
M Mujawar, S Manikandan, M Kalbande… - The Journal of …, 2024 - Springer
Introducing a novel approach for assessing connectivity in dynamic optical networks, we
propose the quantum-driven particle swarm-optimized self-adaptive support vector machine …
propose the quantum-driven particle swarm-optimized self-adaptive support vector machine …
Using SHAP Values to Validate Model's Uncertain Decision for ML-based Lightpath Quality-of-Transmission Estimation
We apply Quantile Regression (QR) for lightpath quality-of-transmission (QoT) estimation
with the aim of identifying uncertain decisions and then exploit Shapley Additive …
with the aim of identifying uncertain decisions and then exploit Shapley Additive …
Artificial Intelligence and Machine Learning in Optical Networking [Tutorial]
C Tremblay - Photonic Networks and Devices, 2024 - opg.optica.org
Artificial Intelligence and Machine Learning in Optical Networking [Tutorial] Page 1 Artificial
Intelligence and Machine Learning in Optical Networking [Tutorial] Christine Tremblay Network …
Intelligence and Machine Learning in Optical Networking [Tutorial] Christine Tremblay Network …