Skip to main content

machine learning; optimization; uncertainty quantification; predictive modeling

Mini-symposium at ASME IMECE 2023 on scientific machine learning and uncertainty quantification

Submitted by danialfaghihi on
conference
machine learning; optimization; uncertainty quantification; predictive modeling

Jessica  Zhang, Alireza Tabarraei, Kathryn Maupin, and myself are organizing a mini-symposium on โ€œData-Enabled Predictive Modeling, Machine Learning, and Uncertainty Quantification in Computational Mechanics,โ€ in the ASME IMECE 2023 (October 29 โ€“ November 2, 2023). The symposium solicits abstracts on novel scientific machine learning (SciML) and uncertainty quantification (UQ) methods a wide range of applications across science, engineering, and medicine.

Subscribe to machine learning; optimization; uncertainty quantification; predictive modeling