Adjoint Schrödinger Bridge Sampler

Computational methods for learning to sample from the Boltzmann distribution-- where the target distribution is known only up to an unnormalized energy function-- have advanced significantly recently. Due to the lack of explicit target samples, however, prior diffusion-based methods, known as diffusion samplers, often require importance-weighted estimation or complicated learning processes.