Assistant Professor, University of Oxford
2 papers at NeurIPS 2025
We present a principled recipe for building graph foundation models that generalize across arbitrary graphs, features, and label spaces.
We learn non-gradient field dynamics by solving Schrödinger Bridge problem with non-zero reference process drift
