PATHFINDER: Multi-objective discovery in structural and spectral spaces

ArXi:2604.04194v1 Announce Type: cross Automated decision-making is becoming key for automated characterization including electron and scanning probe microscopies and nano indentation. Most machine learning driven workflows optimize a single predefined objective and tend to converge prematurely on familiar responses, overlooking rare but scientifically important states.