Control Consistency Losses for Diffusion Bridges
This addresses a challenging problem in the sciences for simulating rare events in diffusion processes, but appears incremental as it builds on existing methods with iterative improvements.
The paper tackles the problem of simulating conditioned dynamics of diffusion processes, particularly for rare events, by leveraging a self-consistency property to learn diffusion bridges iteratively, demonstrating promising empirical results.
Simulating the conditioned dynamics of diffusion processes, given their initial and terminal states, is an important but challenging problem in the sciences. The difficulty is particularly pronounced for rare events, for which the unconditioned dynamics rarely reach the terminal state. In this work, we leverage a self-consistency property of the conditioned dynamics to learn the diffusion bridge in an iterative online manner, and demonstrate promising empirical results in a range of settings.