1.9k citations · 3.9k across the 58 of their papers we have counts for
63 papers
Dynamic language model representations for multi-objective reaction optimisation
Joshua W. Sin, David Ming Segura, Bojana Ranković +8
Optimising chemical reactions across multiple objectives, such as yield, selectivity, and safety, is central to chemical synthesis, and model-driven approaches depend critically on…
Mechanistic Reaction Prediction via Discrete Flow Matching on Graph-Structured Electron Occupation
Nguyen Xuan-Vu, Octavian Susanu, Daniel Armstrong +1
Chemical reactions are fundamentally transformations in electron space, yet most machine learning approaches model them either through de novo generation of product molecules or th…
Strategy-first synthesis planning for complex natural products
Daniel Armstrong, Xuan-Vu Nguyen, Octavian Susanu +15
The total synthesis of a complex molecule is among the most demanding intellectual and experimental feats in chemistry: a chemist must plan many steps ahead for how to assemble sim…
Bi-semantic Chemical Embedder for Joint Representation Learning of SMILES and Natural Language
David Ming Segura, Jeremy Goumaz, Joshua W. Sin +2
Transformer models have revolutionized natural language processing (NLP), and text-based molecular representations like SMILES have successfully extended these architectures to che…
Sample Efficient Generative Optimization for Molecular Design
Sarina Kopf, Cristina Nevado, Philippe Schwaller
Molecular optimization in drug discovery, materials design, and catalysis requires searching vast chemical spaces under tight evaluation budgets, since high-fidelity oracles and ex…
Agentic generation of verifiable rules for deterministic, self-expanding reaction classification
Daniel Armstrong, Maarten Dobbelaere, Valentas Olikauskas +4
Computer-assisted synthesis planning breaks target molecules into accessible precursors using large libraries of reaction rules that assign each transformation a deterministic, int…