Events

Self-driving laboratories can compress years of materials discovery into weeks. Instead of relying on trial-and-error, they use algorithms to learn from each experiment and decide what to try next. When experiments are expensive and budgets are limited, choosing the next experiment well can have a large impact on the quality of the material ultimately discovered. This event will present results from a recent benchmark of 46 data-driven optimization solvers on 502 problems, ranging from one to 300 dimensions and spanning a wide variety of mathematical behavior.