Yuan Tian

Fusing Direct and Indirect Measurements Through Multi‐Fidelity Learning For Accelerated Electrocaloric Materials Discovery

ABSTRACT The data‐driven discovery of high‐performance electrocaloric (EC) materials is challenged by sparse direct measurements and systematic discrepancies between direct and indirect measurements, resulting in heterogeneous datasets with varying fidelity levels. Here, a co‐kriging‐based multi‐fidelity learning frame...