SELFIES: a robust representation of semantically constrained graphs with an example application in chemistry. - Mario Krenn; Florian Häse; AkshatKumar Nigam; Pascal Friederich; Alán Aspuru-Guzik (CoRR, 2019)

Augmenting Genetic Algorithms with Deep Neural Networks for Exploring the Chemical Space. - AkshatKumar Nigam; Pascal Friederich; Mario Krenn; Alán Aspuru-Guzik (ICLR, 2020)

Curiosity in exploring chemical space: Intrinsic rewards for deep molecular reinforcement learning. - Luca A. Thiede; Mario Krenn; AkshatKumar Nigam; Alán Aspuru-Guzik (CoRR, 2020)

Self-referencing embedded strings (SELFIES): A 100% robust molecular string representation. - Mario Krenn; Florian Häse; AkshatKumar Nigam; Pascal Friederich; Alán Aspuru-Guzik (Mach. Learn. Sci. Technol., 2020)

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)

Curiosity in exploring chemical spaces: intrinsic rewards for molecular reinforcement learning. - Luca A. Thiede; Mario Krenn; AkshatKumar Nigam; Alán Aspuru-Guzik (Mach. Learn. Sci. Technol., 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)

Quantum Computing-Enhanced Algorithm Unveils Novel Inhibitors for KRAS. - Mohammad Ghazi Vakili; Christoph Gorgulla; AkshatKumar Nigam; Dmitry Bezrukov; Daniel Varoli; Alex Aliper; Daniil Polykovskiy; Krishna M. Padmanabha Das; Jamie Snider; Anna Lyakisheva; Ardalan Hosseini Mansob; Zhong Yao; et al. (CoRR, 2024)