Benchmarking the Performance of Bayesian Optimization across Multiple Experimental Materials Science Domains. - Qiaohao Liang; Aldair E. Gongora; Zekun Ren; Armi Tiihonen; Zhe Liu 040; Shijing Sun; James R. Deneault; Daniil Bash; Flore Mekki-Berrada; Saif A. Khan; Kedar Hippalgaonkar; Benji Maruyama; et al. (CoRR, 2021)

Opportunities for Machine Learning to Accelerate Halide Perovskite Commercialization and Scale-Up. - Rishi E. Kumar; Armi Tiihonen; Shijing Sun; David P. Fenning; Zhe Liu 040; Tonio Buonassisi (CoRR, 2021)

Vision-driven Autocharacterization of Perovskite Semiconductors. - Alexander E. Siemenn; Eunice Aissi; Fang Sheng; Armi Tiihonen; Hamide Kavak; Basita Das; Tonio Buonassisi (CoRR, 2023)

Cost-aware learning of relevant contextual variables within Bayesian optimization. - Julien Martinelli; Ayush Bharti; S. T. John; Armi Tiihonen; Sabina Sloman; Louis Filstroff; Samuel Kaski (CoRR, 2023)

Learning relevant contextual variables within Bayesian optimization. - Julien Martinelli; Ayush Bharti; Armi Tiihonen; S. T. John; Louis Filstroff; Sabina J. Sloman; Patrick Rinke; Samuel Kaski (UAI, 2024)

Batch Bayesian Optimization for High-Dimensional Experimental Design: Simulation and Visualization. - Imon Mia; Armi Tiihonen; Anna Ernst; Anusha Srivastava; Tonio Buonassisi; William G. Vandenberghe; Julia W. P. Hsu (CoRR, 2025)

Virtual Laboratories: Domain-agnostic workflows for research. - Carlos Sevilla-Salcedo; Armi Tiihonen; Mahsa Asadi; Kevin Sebastian Luck; Aras Umut Erarslan; Arto Klami; Samuel Kaski (CoRR, 2025)