Benjamín Sánchez-Lengeling

According to our database, Benjamín Sánchez-Lengeling authored at least 17 papers between 2017 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2026

Gradient-based optimization of complex nanoparticle heterostructures enabled by deep learning on heterogeneous graphs.

Eric Sivonxay, Lucas Attia, Evan Walter Clark Spotte-Smith, Benjamín Sánchez-Lengeling, Xiaojing Xia, Daniel Barter, Emory M. Chan, Samuel M. Blau

Nat. Comput. Sci., January, 2026

2025

AI for Sustainable Future Foods.

Bianca Datta, Markus J. Buehler, Yvonne Chow, Kristina Gligoric, Dan Jurafsky, David L. Kaplan, Rodrigo Ledesma-Amaro, Giorgia Del Missier, Lisa Neidhardt, Karim Pichara, Benjamín Sánchez-Lengeling, Miek Schlangen, Skyler R. St. Pierre, Ilias Tagkopoulos, Anna T. Thomas, Nicholas James Watson, Ellen Kuhl

CoRR, September, 2025

Graph Data Modeling: Molecules, Proteins, & Chemical Processes.

José Manuel Barraza-Chavez, Rana Ahmed Barghout, Ricardo Almada-Monter, Adrian Jinich, Radhakrishnan Mahadevan, Benjamín Sánchez-Lengeling

CoRR, August, 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, June, 2025

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, January, 2025

Does this smell the same? Learning representations of olfactory mixtures using inductive biases.

Gary Tom, Cher Tian Ser, Ella M. Rajaonson, Stanley Lo, Hyun Suk Park, Brian K. Lee, Benjamín Sánchez-Lengeling

Mach. Learn. Sci. Technol., 2025

2024

Ranking over Regression for Bayesian Optimization and Molecule Selection.

Gary Tom, Stanley Lo, Samantha Corapi, Alán Aspuru-Guzik, Benjamín Sánchez-Lengeling

CoRR, 2024

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

2022

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

2021

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

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

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

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019

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

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

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

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, Alán Aspuru-Guzik, Alex Zhavoronkov

CoRR, 2018

2017

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