Explores the quasi-stationary distribution approach in molecular dynamics modeling, covering Langevin dynamics, metastability, and kinetic Monte Carlo models.
Discusses metastability, phase transitions, approximate message passing algorithm limitations, and the efficiency of Langevin dynamics in high-dimensional inference.
Explores the connection between phase transitions in physics and computational problems, showcasing how insights from physics can inform algorithm design.