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A hardware efficient quantum residual neural network without post-selection
Amena Khatun, Akib Karim, Muhammad Usman
We propose a hardware efficient quantum residual neural network which implements residual connections through a deterministic mixture of the identity operation and variational unit…
Adversarially Robust Quantum Transfer Learning
Amena Khatun, Muhammad Usman
Quantum machine learning (QML) has emerged as a promising area of research for enhancing the performance of classical machine learning systems by leveraging quantum computational p…
Classical Autoencoder Distillation of Quantum Adversarial Manipulations
Amena Khatun, Muhammad Usman
Quantum neural networks have been proven robust against classical adversarial attacks, but their vulnerability against quantum adversarial attacks is still a challenging problem. H…
Quantum Generative Learning for High-Resolution Medical Image Generation
Amena Khatun, Kübra Yeter Aydeniz, Yaakov S. Weinstein +1
Integration of quantum computing in generative machine learning models has the potential to offer benefits such as training speed-up and superior feature extraction. However, the e…
Quantum Transfer Learning with Adversarial Robustness for Classification of High-Resolution Image Datasets
Amena Khatun, Muhammad Usman
The application of quantum machine learning to large-scale high-resolution image datasets is not yet possible due to the limited number of qubits and relatively high level of noise…