Objective-Reinforced Generative Adversarial Networks (ORGAN) for Sequence Generation Models. - Gabriel Lima Guimaraes; Benjamín Sánchez-Lengeling; Pedro Luis Cunha Farias; Alán Aspuru-Guzik (CoRR, 2017)

Molecular Sets (MOSES): A Benchmarking Platform for Molecular Generation Models. - Daniil Polykovskiy; Alexander Zhebrak; Benjamín Sánchez-Lengeling; Sergey Golovanov; Oktai Tatanov; Stanislav Belyaev; Rauf Kurbanov; Aleksey Artamonov; Vladimir Aladinskiy; Mark Veselov; Artur Kadurin; Sergey I. Nikolenko; et al. (CoRR, 2018)

Reinforced Adversarial Neural Computer for de Novo Molecular Design. - Evgeny Putin; Arip Asadulaev; Yan Ivanenkov; Vladimir Aladinskiy; Benjamín Sánchez-Lengeling; Alán Aspuru-Guzik; Alex Zhavoronkov (J. Chem. Inf. Model., 2018)

Quantum chemistry reveals thermodynamic principles of redox biochemistry. - Adrian Jinich; Avi I. Flamholz; Haniu Ren; Sungjin Kim; Benjamín Sánchez-Lengeling; Charles A. R. Cotton; Elad Noor; Alán Aspuru-Guzik; Arren Bar-Even (PLoS Comput. Biol., 2018)

Machine Learning for Scent: Learning Generalizable Perceptual Representations of Small Molecules. - Benjamín Sánchez-Lengeling; Jennifer N. Wei; Brian K. Lee; Richard C. Gerkin; Alán Aspuru-Guzik; Alexander B. Wiltschko (CoRR, 2019)

Evaluating Attribution for Graph Neural Networks. - Benjamín Sánchez-Lengeling; Jennifer N. Wei; Brian K. Lee; Emily Reif; Peter Wang; Wesley Wei Qian; Kevin McCloskey; Lucy J. Colwell; Alexander B. Wiltschko (NeurIPS, 2020)

A machine learning workflow for molecular analysis: application to melting points. - Ganesh Sivaraman; Nicholas E. Jackson; Benjamín Sánchez-Lengeling; Álvaro Vázquez-Mayagoitia; Alán Aspuru-Guzik; Venkatram Vishwanath; Juan J. de Pablo (Mach. Learn. Sci. Technol., 2020)

Inverse design of nanoporous crystalline reticular materials with deep generative models. - Zhenpeng Yao; Benjamín Sánchez-Lengeling; N. Scott Bobbitt; Benjamin J. Bucior; Sai Govind Hari Kumar; Sean P. Collins; Thomas Burns; Tom K. Woo; Omar K. Farha; Randall Q. Snurr; Alán Aspuru-Guzik (Nat. Mach. Intell., 2021)

Calibration and generalizability of probabilistic models on low-data chemical datasets with DIONYSUS. - Gary Tom; Riley J. Hickman; Aniket Zinzuwadia; Afshan Mohajeri; Benjamín Sánchez-Lengeling; Alán Aspuru-Guzik (CoRR, 2022)

Advancing Molecular Machine (Learned) Representations with Stereoelectronics-Infused Molecular Graphs. - Daniil A. Boiko; Thiago Reschützegger; Benjamín Sánchez-Lengeling; Samuel M. Blau; Gabe Gomes (CoRR, 2024)

Ranking over Regression for Bayesian Optimization and Molecule Selection. - Gary Tom; Stanley Lo; Samantha Corapi; Alán Aspuru-Guzik; Benjamín Sánchez-Lengeling (CoRR, 2024)

From Molecules to Mixtures: Learning Representations of Olfactory Mixture Similarity using Inductive Biases. - Gary Tom; Cher Tian Ser; Ella M. Rajaonson; Stanley Lo; Hyun Suk Park; Brian K. Lee; Benjamín Sánchez-Lengeling (CoRR, 2025)

CheMixHub: Datasets and Benchmarks for Chemical Mixture Property Prediction. - Ella M. Rajaonson; Mahyar Rajabi Kochi; Luis Martin Mejia Mendoza; Seyed Mohamad Moosavi; Benjamín Sánchez-Lengeling (CoRR, 2025)