3 papers
quant-ph2026
Hybrid Quantum Neural Networks: Theory, Implementations, and Applications
Léo Monbroussou, Maniraman Periyasamy, Viacheslav Kuzmin +4
Artificial intelligence has been transformed by deep neural networks, yet the search for new learning architectures continues. Quantum machine learning offers one such direction, a…
quant-ph2026
Shot-based quantum encoding: a data-loading paradigm for quantum neural networks
Basil Kyriacou, Viktoria Patapovich, Maniraman Periyasamy +1
Efficient data loading remains a bottleneck for near-term quantum machine learning. Existing schemes (angle, amplitude, and basis encoding) either underuse the exponential Hilbert-…
quant-ph2026
Superposed parameterised quantum circuits
Viktoria Patapovich, Maniraman Periyasamy, Mo Kordzanganeh +1
Quantum machine learning has shown promise for high-dimensional data analysis, yet many existing approaches rely on linear unitary operations and shared trainable parameters across…