Optimal quantum kernels for small data classification. - Elham Torabian; Roman V. Krems (CoRR, 2022)

Universal expressiveness of variational quantum classifiers and quantum kernels for support vector machines. - Jonas Jäger; Roman V. Krems (CoRR, 2022)

Gradient domain machine learning with composite kernels: improving the accuracy of PES and force fields for large molecules. - Kasra Asnaashari; Roman V. Krems (Mach. Learn. Sci. Technol., 2022)

Efficient interpolation of molecular properties across chemical compound space with low-dimensional descriptors. - Yun-Wen Mao; Roman V. Krems (CoRR, 2023)

Neural network Gaussian processes as efficient models of potential energy surfaces for polyatomic molecules. - Jun Dai; Roman V. Krems (Mach. Learn. Sci. Technol., 2023)

Benchmarking of quantum fidelity kernels for Gaussian process regression. - Xuyang Guo; Jun Dai; Roman V. Krems (Mach. Learn. Sci. Technol., 2024)