Learn how to leverage generative AI to support and improve your productivity at work. The next cohort will take place online on April 28 and 30, 2026, in French.
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Generating novel molecules with optimal properties is a crucial step in many industries such as drug discovery. Recently, deep generative mo… (see more)dels have shown a promising way of performing de-novo molecular design. Although graph generative models are currently available they either have a graph size dependency in their number of parameters, limiting their use to only very small graphs or are formulated as a sequence of discrete actions needed to construct a graph, making the output graph non-differentiable w.r.t the model parameters, therefore preventing them to be used in scenarios such as conditional graph generation. In this work we propose a model for conditional graph generation that is computationally efficient and enables direct optimisation of the graph. We demonstrate favourable performance of our model on prototype-based molecular graph conditional generation tasks.