papers

Publications (8)

q-bio.BM2025

Procedural Synthesis of Synthesizable Molecules

Michael Sun, Alston Lo, Minghao Guo +3

Designing synthetically accessible molecules and recommending analogs to unsynthesizable molecules are important problems for accelerating molecular discovery. We reconceptualize b…

cs.LG2026

Fast Organic Crystal Structure Prediction with Unit Cell Flow Matching

Alston Lo, Luka Mucko, Austin H. Cheng +4

Organic crystal structure prediction (CSP) is a requirement for computational modelling of organic solids, but traditionally costs several CPU-years per molecule. Generative models…

physics.chem-ph2022

SELFIES and the future of molecular string representations

Mario Krenn, Qianxiang Ai, Senja Barthel +28

Artificial intelligence (AI) and machine learning (ML) are expanding in popularity for broad applications to challenging tasks in chemistry and materials science. Examples include…

cs.LG2026

A Genetic Algorithm for Navigating Synthesizable Molecular Spaces

Alston Lo, Connor W. Coley, Wojciech Matusik

Inspired by the effectiveness of genetic algorithms and the importance of synthesizability in molecular design, we present SynGA, a simple genetic algorithm that operates directly…

cs.LG2025

Stiefel Flow Matching for Moment-Constrained Structure Elucidation

Austin Cheng, Alston Lo, Kin Long Kelvin Lee +2

Molecular structure elucidation is a fundamental step in understanding chemical phenomena, with applications in identifying molecules in natural products, lab syntheses, forensic s…

cs.LG2023

Reflection-Equivariant Diffusion for 3D Structure Determination from Isotopologue Rotational Spectra in Natural Abundance

Austin Cheng, Alston Lo, Santiago Miret +2

Structure determination is necessary to identify unknown organic molecules, such as those in natural products, forensic samples, the interstellar medium, and laboratory syntheses.…

cs.LG2022

If Influence Functions are the Answer, Then What is the Question?

Juhan Bae, Nathan Ng, Alston Lo +2

Influence functions efficiently estimate the effect of removing a single training data point on a model's learned parameters. While influence estimates align well with leave-one-ou…

physics.chem-ph2023

Recent advances in the Self-Referencing Embedding Strings (SELFIES) library

Alston Lo, Robert Pollice, AkshatKumar Nigam +3

String-based molecular representations play a crucial role in cheminformatics applications, and with the growing success of deep learning in chemistry, have been readily adopted in…