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quant-ph2025
QCA-MolGAN: Quantum Circuit Associative Molecular GAN with Multi-Agent Reinforcement Learning
Aaron Mark Thomas, Yu-Cheng Chen, Hubert Okadome Valencia +2
Navigating the vast chemical space of molecular structures to design novel drug molecules with desired target properties remains a central challenge in drug discovery. Recent advan…
quant-ph2025
VAE-QWGAN: Addressing Mode Collapse in Quantum GANs via Autoencoding Priors
Aaron Mark Thomas, Harry Youel, Sharu Theresa Jose
Recent proposals for quantum generative adversarial networks (GANs) suffer from the issue of mode collapse, analogous to classical GANs, wherein the distribution learnt by the GAN…
quant-ph2025
On the Generalization of Adversarially Trained Quantum Classifiers
Petros Georgiou, Aaron Mark Thomas, Sharu Theresa Jose +1
Quantum classifiers are vulnerable to adversarial attacks that manipulate their input classical or quantum data. A promising countermeasure is adversarial training, where quantum c…