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2020 – present
- Chandrika Kamath, “Intelligent Sampling for Surrogate Modeling, Hyperparameter Optimization, and Data Analysis, ” LLNL Technical Report LLNL-TR-829837, December 2021.
- Chandrika Kamath, Juliette Franzman, and Ravi Ponmalai, “Data mining for faster, interpretable solutions to inverse problems: A case study using additive manufacturing,” Machine Learning with Applications, Volume 6, 15 December 2021, https://doi.org/10.1016/j.mlwa.2021.100122.
- A. Buluc, T. G. Kolda, S. M. Wild, M. Anitescu, A. DeGennaro, J. Jakeman, C. Kamath, R. Kannan, M. E. Lopes, P.-G. Martinsson, K. Myers, J. Nelson, J. M. Restrepo, C. Seshadhri, D. Vrabie, B. Wohlberg, S. J. Wright, C. Yang, P. Zwart, “Randomized Algorithms for Scientific Computing (RASC)”, arXiv:2104.11079, April 2021.
- Juliette Franzman, “Understanding the Effects of Tapering on Gaussian Process Regression,” student poster, Student and Post-Doc Poster Session, Conference on Data Analysis, February 25-27, 2020, Santa Fe, New Mexico.
- Ravi Brannon Ponmalai, “Self-Organizing Maps and Their Applications to Data Analysis,” student poster, Student and Post-Doc Poster Session, Conference on Data Analysis, February 25-27, 2020, Santa Fe, New Mexico. Honorable Mention.
- Chandrika Kamath, “Building High-Density, Additively-Manufactured Metal Parts – A Retrospective Look From a Data Analysis Perspective”, invited presentation, Conference on Data Analysis, February 25-27, 2020, Santa Fe, New Mexico.
- C. Kamath, “Compressing unstructured mesh data from simulations using machine learning,” International Journal of Data Science and Analytics, Volume 9, pp 113-130, (2020) https://doi.org/10.1007/s41060-019-00180-6