This paper introduces hyperbolic space into dataset distillation for the first time.

We introduce Momentum Multi-Marginal Schrödinger Bridge Matching (3MSBM), a novel matching framework that learns smooth trajectories for stochastic systems that satisfy multiple positional constraints.