activity
20222026
most citedSELFIES and the future of molecular string representations

292 citations · 341 across the 8 of their papers we have counts for

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Showing cs.LGShow all

6 papers · 1 filter

cs.LG2026

Scientific Discovery under Validation Congestion via Multi-Fidelity Pairwise Rankings

Kevin Tirta Wijaya, Alston Lo, Michael Sun +2

Modern computational methods can now propose candidate molecules, materials, and other scientific designs at an unprecedented scale, creating a validation congestion where candidat…

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…

cs.LG2025★ 1 cited

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.LG2024★ 2 cited

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★ 9 cited

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★ 12 cited

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…