121 citations · 130 across the 4 of their papers we have counts for
5 papers · 1 filter
SynLaD: Latent Diffusion for Generating Synthesizable Molecules Conditioned on 3D Pharmacophore Profiles
Miruna Cretu, John Bradshaw, Patricia Suriana +6
We present SynLaD, a latent diffusion framework for small-molecule generation that unifies ligand-based drug design objectives (what to make) with synthetic accessibility (how to m…
Evaluating the Progression of Large Language Model Capabilities for Small-Molecule Drug Design
Shriram Chennakesavalu, Kirill Shmilovich, Hayley Weir +5
Large Language Models (LLMs) have the potential to accelerate small molecule drug design due to their ability to reason about information from diverse sources and formats. However,…
Barking up the right tree: an approach to search over molecule synthesis DAGs
John Bradshaw, Brooks Paige, Matt J. Kusner +2
When designing new molecules with particular properties, it is not only important what to make but crucially how to make it. These instructions form a synthesis directed acyclic gr…
A Model to Search for Synthesizable Molecules
John Bradshaw, Brooks Paige, Matt J. Kusner +2
Deep generative models are able to suggest new organic molecules by generating strings, trees, and graphs representing their structure. While such models allow one to generate mole…
Are Generative Classifiers More Robust to Adversarial Attacks?
Yingzhen Li, John Bradshaw, Yash Sharma
There is a rising interest in studying the robustness of deep neural network classifiers against adversaries, with both advanced attack and defence techniques being actively develo…