ChemOS: Orchestrating autonomous experimentation. - Florian Häse; Christoph Kreisbeck; Teresa Tamayo-Mendoza; Lars P. E. Yunker; Jason E. Hein; Alán Aspuru-Guzik (Sci. Robotics, 2018)

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)

Gryffin: An algorithm for Bayesian optimization for categorical variables informed by physical intuition with applications to chemistry. - Florian Häse; Loïc M. Roch; 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)

Gemini: Dynamic Bias Correction for Autonomous Experimentation and Molecular Simulation. - Riley J. Hickman; Florian Häse; Loïc M. Roch; Alán Aspuru-Guzik (CoRR, 2021)

Golem: An algorithm for robust experiment and process optimization. - Matteo Aldeghi; Florian Häse; Riley J. Hickman; Isaac Tamblyn; Alán Aspuru-Guzik (CoRR, 2021)

Olympus: a benchmarking framework for noisy optimization and experiment planning. - Florian Häse; Matteo Aldeghi; Riley J. Hickman; Loïc M. Roch; Melodie Christensen; Elena Liles; Jason E. Hein; Alán Aspuru-Guzik (Mach. Learn. Sci. Technol., 2021)

Bayesian optimization with known experimental and design constraints for chemistry applications. - Riley J. Hickman; Matteo Aldeghi; Florian Häse; Alán Aspuru-Guzik (CoRR, 2022)

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)