Quantum Orthogonal Neural Networks for Medical Image Classification
An orthogonal neural network architecture built from quantum gates, with an efficient training algorithm
Joint work with F. Hoffmann-La Roche AG.
Designed an orthogonal neural network architecture using quantum gates and an efficient learning algorithm to train perfectly orthogonal neural networks, then extended it to an actual quantum architecture and benchmarked its performance on Medical MNIST image classification (Landman et al., 2022).
References
2022
- QuantumQuantum methods for neural networks and application to medical image classificationQuantum, 2022