Graph In-Context Operator Networks for Generalizable Spatiotemporal Prediction

ArXi:2603.12725v1 Announce Type: cross In-context operator learning enables neural networks to infer solution operators from contextual examples without weight updates. While prior work has nstrated the effectiveness of this paradigm in leveraging vast datasets, a systematic comparison against single-operator learning using identical