Fast Kinetic Monte Carlo Simulations Using Hash Table Based Caching with Applications to Nanowire Growth and Sintering. - Kristofer G. Reyes (Multiscale Model. Simul., 2014)

Optimal Learning in Experimental Design Using the Knowledge Gradient Policy with Application to Characterizing Nanoemulsion Stability. - Si Chen; Kristofer-Roy G. Reyes; Maneesh K. Gupta; Michael C. McAlpine; Warren B. Powell (SIAM/ASA J. Uncertain. Quantification, 2015)

Nested-Batch-Mode Learning and Stochastic Optimization with An Application to Sequential MultiStage Testing in Materials Science. - Yingfei Wang; Kristofer G. Reyes; Keith A. Brown; Chad A. Mirkin; Warren B. Powell (SIAM J. Sci. Comput., 2015)

A Knowledge Gradient Policy for Sequencing Experiments to Identify the Structure of RNA Molecules Using a Sparse Additive Belief Model. - Yan Li 013; Kristofer G. Reyes; Jorge Vazquez-Anderson; Yingfei Wang; Lydia M. Contreras; Warren B. Powell (INFORMS J. Comput., 2018)

Optimal Learning for Sequential Decisions in Laboratory Experimentation. - Kristofer G. Reyes; Warren B. Powell (CoRR, 2020)

Optimal Learning with Local Nonlinear Parametric Models over Continuous Designs. - Xinyu He; Kristofer G. Reyes; Warren B. Powell (SIAM J. Sci. Comput., 2020)

Self-Driven Multistep Quantum Dot Synthesis Enabled by Autonomous Robotic Experimentation in Flow. - Kameel Abdel-Latif; Robert W. Epps; Fazel Bateni; Suyong Han; Kristofer G. Reyes; Milad Abolhasani (Adv. Intell. Syst., 2021)

Problem-fluent models for complex decision-making in autonomous materials research. - Soojung Baek; Kristofer G. Reyes (CoRR, 2021)

Autonomous Nanocrystal Doping by Self-Driving Fluidic Micro-Processors. - Fazel Bateni; Robert Epps; Kameel Abdel-Latif; Rokas Dargis; Jeffery A. Bennett; Kristofer G. Reyes; Milad Abolhasani (Adv. Intell. Syst., 2022)

Autonomous Nanocrystal Doping by Self-Driving Fluidic Micro-Processors. - Fazel Bateni; Robert W. Epps; Kameel Antami; Rokas Dargis; Jeffery A. Bennett; Kristofer G. Reyes; Milad Abolhasani (Adv. Intell. Syst., 2022)

Exact Gaussian Processes for Massive Datasets via Non-Stationary Sparsity-Discovering Kernels. - Marcus Michael Noack; Harinarayan Krishnan; Mark D. Risser; Kristofer G. Reyes (CoRR, 2022)

A Rigorous Uncertainty-Aware Quantification Framework Is Essential for Reproducible and Replicable Machine Learning Workflows. - Line Pouchard; Kristofer G. Reyes; Francis J. Alexander; Byung-Jun Yoon (CoRR, 2023)

Pessimistic asynchronous sampling in high-cost Bayesian optimization. - Amanda A. Volk; Kristofer G. Reyes; Jeffrey G. Ethier; Luke A. Baldwin (CoRR, 2024)