A residual-based continuity loss for Wasserstein gradient flows yields a simulation-free stitching method robust to sparse observations and state-of-the-art on trajectory inference benchmarks.
Flow models relate to Schrödinger dynamics via an unusual Hamiltonian, enabling efficient quantum Hamiltonian simulation for preparing coherent encodings of flow-modeled distributions and supporting quantum statistical algorithms.