2 citations · 2 across the 2 of their papers we have counts for
2 papers
quant-ph2026
Benchmarking Quantum Kernel Support Vector Machines Against Classical Baselines on Tabular Data: A Rigorous Empirical Study with Hardware Validation
Siavash Kakavand, Christoph Strohmeyer, Michael Schlotter
Quantum kernel methods have been proposed as a promising approach for leveraging near-term quantum computers for supervised learning, yet rigorous benchmarks against strong classic…
cs.LG2024★ 2 cited
OpTC -- A Toolchain for Deployment of Neural Networks on AURIX TC3xx Microcontrollers
Christian Heidorn, Frank Hannig, Dominik Riedelbauch +2
The AURIX 2xx and 3xx families of TriCore microcontrollers are widely used in the automotive industry and, recently, also in applications that involve machine learning tasks. Yet,…