Xianglong Hou

CFO: Learning Continuous-Time PDE Dynamics via Flow-Matched Neural Operators

Neural operator surrogates for time-dependent partial differential equations (PDEs) conventionally employ autoregressive prediction schemes, which accumulate error over long rollouts and require uniform temporal discretization. We introduce the Continuous Flow Operator (CFO), a framework that learns…