Latent Style-based Quantum Wasserstein GAN for Drug Design
The development of new drugs is a tedious, time-consuming, and expensive process, for which the average costs are estimated to be up to around $2.5 billion. The first step in this long process is the design of the new drug, for which de novo drug design, assisted by artificial intelligence, has blossomed in recent years and revolutionized the field. In particular, generative artificial intelligence has delivered promising results in drug discovery and development, reducing costs and the time to solution. However, classical generative models, such as generative adversarial networks (GANs), are difficult to train due to barren plateaus and prone to mode collapse. Quantum computing may be an...
| Authors | Julien Baglio, Yacine Haddad, Richard Polifka |
|---|---|
| Primary category | quant-ph |
| Published | 23 March 2026 |
| Last updated at source | 23 March 2026 |
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