Stathis Zavvos

Quantum Neural Networks: A Path to Lower Emissions Through Fuel Consumption Prediction in Shipping

This paper proposes Quantum Neural Networks (QNNs) as a data-driven approach for predicting fuel consumption. We utilize various layer architecture designs available in the Torchquantum framework, including both entangled and non-entangled circuit designs. In general, QNNs can achieve comparable Roo…