Broadly speaking, an energy landscape is the graph of a loss function over a parameter space.  Some examples include the potential energy landscape of a chemical reaction, measuring the fitness of a mechanism to perform many tasks, and a loss function arising from a training set in machine learning.  This talk will discuss some successes of using computational techniques arising in numerical algebraic geometry to analyze both polynomial and non-polynomial energy landscapes arising in science and engineering applications.

Recorded Zoom Talk