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Riley J. Hickman
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Data-driven strategies for accelerated materials design
R Pollice, G dos Passos Gomes, M Aldeghi, RJ Hickman, M Krenn, ...
Accounts of Chemical Research 54 (4), 849-860, 2021
1062021
Gryffin: An algorithm for Bayesian optimization of categorical variables informed by expert knowledge
F Häse, M Aldeghi, RJ Hickman, LM Roch, A Aspuru-Guzik
Applied Physics Reviews 8 (3), 031406, 2021
412021
Olympus: a benchmarking framework for noisy optimization and experiment planning
F Häse, M Aldeghi, RJ Hickman, LM Roch, M Christensen, E Liles, ...
Machine Learning: Science and Technology 2 (3), 035021, 2021
332021
Assigning confidence to molecular property prediction
AK Nigam, R Pollice, MFD Hurley, RJ Hickman, M Aldeghi, N Yoshikawa, ...
Expert opinion on drug discovery 16 (9), 1009-1023, 2021
212021
General Formalism of Vibronic Hamiltonians for Tetrahedral and Octahedral Systems: Problems That Involve T, E States and t, e Vibrations
T Zeng, RJ Hickman, A Kadri, I Seidu
Journal of Chemical Theory and Computation 13 (10), 5004-5018, 2017
152017
Golem: An algorithm for robust experiment and process optimization
M Aldeghi, F Häse, RJ Hickman, I Tamblyn, A Aspuru-Guzik
Chemical science 12 (44), 14792-14807, 2021
122021
General formalism for vibronic Hamiltonians in tetragonal symmetry and beyond
RJ Hickman, RA Lang, T Zeng
Physical Chemistry Chemical Physics 20 (17), 12312-12322, 2018
112018
Optical monitoring of polymerizations in droplets with high temporal dynamic range
AC Cavell, VK Krasecki, G Li, A Sharma, H Sun, MP Thompson, ...
Chemical science 11 (10), 2647-2656, 2020
82020
Routescore: Punching the ticket to more efficient materials development
M Seifrid, RJ Hickman, A Aguilar-Granda, C Lavigne, J Vestfrid, TC Wu, ...
ACS central science 8 (1), 122-131, 2022
52022
A molecular computing approach to solving optimization problems via programmable microdroplet arrays
SY Guo, P Friederich, Y Cao, TC Wu, CJ Forman, D Mendoza, ...
Matter 4 (4), 1107-1124, 2021
52021
Gemini: Dynamic bias correction for autonomous experimentation and molecular simulation
RJ Hickman, F Häse, LM Roch, A Aspuru-Guzik
arXiv preprint arXiv:2103.03391, 2021
42021
VHEGEN: A vibronic Hamiltonian expansion generator for trigonal and tetragonal polyatomic systems
RA Lang, RJ Hickman, T Zeng
Computer Physics Communications, 2019
42019
Bayesian optimization with known experimental and design constraints for chemistry applications
RJ Hickman, M Aldeghi, F Häse, A Aspuru-Guzik
arXiv preprint arXiv:2203.17241, 2022
32022
Equipping data-driven experiment planning for Self-driving Laboratories with semantic memory: case studies of transfer learning in chemical reaction optimization
R Hickman, J Ruža, L Roch, H Tribukait, A García-Durán
12022
Molar
T Gaudin, I Benlolo, Z Yu Cui, R Hickman, I Tamblyn, A Aspuru-Guzik
10.5281/zenodo.6809291, 2022
2022
Machine Learning Models to Accelerate the Design of Polymeric Long-Acting Injectables
P Bannigan, Z Bao, R Hickman, M Aldeghi, F Häse, A Aspuru-Guzik, ...
2022
Automated generation of benchmark sets guided by a Bayesian decision maker
C Stein, J Proppe, T Gaudin, R Hickman, M Head-Gordon, ...
ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY 258, 2019
2019
General formalism for vibronic Hamiltonians in tetragonal symmetry and beyond
T Zeng, RJ Hickman, R Lang
Royal Society of Chemistry, 2018
2018
General formalism for vibronic Hamiltonians in tetragonal symmetry and beyond Supporting Information
RJ Hickman, RA Lang, T Zeng
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Articles 1–19