2 papers
quant-ph2026
Reduced Cost Quantum Kernel Training
Daniel R. Germain, Benjamin Goldweber, Kayla J. Rodriguez +1
Quantum kernel methods are promising for near-term quantum machine learning, but their training costs are driven by the quadratic scaling of Gram-matrix construction and the measur…
quant-ph2026
Quantum Enhanced Deep Reinforcement Learning for Distribution Network Reconfiguration
Daniel Germain, Mason Blanchard, Audrey Versteegen +5
Modern smart grids generate increasingly rich operational data and deploy greater numbers of remotely controlled switching assets than ever before, creating new opportunities for d…