Assigning Confidence to Molecular Property Prediction. - AkshatKumar Nigam; Robert Pollice; Matthew F. D. Hurley; Riley J. Hickman; Matteo Aldeghi; Naruki Yoshikawa; Seyone Chithrananda; Vincent A. Voelz; Alán Aspuru-Guzik (CoRR, 2021)

JANUS: Parallel Tempered Genetic Algorithm Guided by Deep Neural Networks for Inverse Molecular Design. - AkshatKumar Nigam; Robert Pollice; Alán Aspuru-Guzik (CoRR, 2021)

On scientific understanding with artificial intelligence. - Mario Krenn; Robert Pollice; Si Yue Guo; Matteo Aldeghi; Alba Cervera-Lierta; Pascal Friederich; Gabriel dos Passos Gomes; Florian Häse; Adrian Jinich; AkshatKumar Nigam; Zhenpeng Yao; Alán Aspuru-Guzik (CoRR, 2022)

Tartarus: A Benchmarking Platform for Realistic And Practical Inverse Molecular Design. - AkshatKumar Nigam; Robert Pollice; Gary Tom; Kjell Jorner; Luca A. Thiede; Anshul Kundaje; Alán Aspuru-Guzik (CoRR, 2022)

SELFIES and the future of molecular string representations. - 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; et al. (Patterns, 2022)

Tartarus: A Benchmarking Platform for Realistic And Practical Inverse Molecular Design. - AkshatKumar Nigam; Robert Pollice; Gary Tom; Kjell Jorner; John Willes; Luca A. Thiede; Anshul Kundaje; Alán Aspuru-Guzik (NeurIPS, 2023)

Recent advances in the Self-Referencing Embedding Strings (SELFIES) library. - Alston Lo; Robert Pollice; AkshatKumar Nigam; Andrew D. White; Mario Krenn; Alán Aspuru-Guzik (CoRR, 2023)

Show, Don't Tell: Evaluating Large Language Models Beyond Textual Understanding with ChildPlay. - Gonçalo Hora de Carvalho; Robert Pollice; Oscar Knap (CoRR, 2024)