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

1 code implementation • 17 Oct 2023 • Austin Cheng, Alston Lo, Santiago Miret, Brooks Pate, Alán Aspuru-Guzik

KREED's top-1 predictions identify the correct 3D structure with >98% accuracy on the QM9 and GEOM datasets when provided with substitution coordinates of all heavy atoms with natural isotopic abundance.

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

1 code implementation • 7 Feb 2023 • Alston Lo, Robert Pollice, AkshatKumar Nigam, Andrew D. White, Mario Krenn, Alán Aspuru-Guzik

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 into machine learning pipelines.

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

2 code implementations • 12 Sep 2022 • Juhan Bae, Nathan Ng, Alston Lo, Marzyeh Ghassemi, Roger Grosse

Influence functions efficiently estimate the effect of removing a single training data point on a model's learned parameters.

SELFIES and the future of molecular string representations

1 code implementation • 31 Mar 2022 • Mario Krenn, Qianxiang Ai, Senja Barthel, Nessa Carson, Angelo Frei, Nathan C. Frey, Pascal Friederich, Théophile Gaudin, Alberto Alexander Gayle, Kevin Maik Jablonka, Rafael F. Lameiro, Dominik Lemm, Alston Lo, Seyed Mohamad Moosavi, José Manuel Nápoles-Duarte, AkshatKumar Nigam, Robert Pollice, Kohulan Rajan, Ulrich Schatzschneider, Philippe Schwaller, Marta Skreta, Berend Smit, Felix Strieth-Kalthoff, Chong Sun, Gary Tom, Guido Falk von Rudorff, Andrew Wang, Andrew White, Adamo Young, Rose Yu, Alán Aspuru-Guzik

We hope that these proposals will inspire several follow-up works exploiting the full potential of molecular string representations for the future of AI in chemistry and materials science.

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