Diffusion bridges (DB) have emerged as a promising alternative to diffusion models for
imaging inverse problems, achieving faster sampling by directly bridging low-and high …

Depth completion upgrades sparse depth measurements into dense depth maps guided by
a conventional image. Existing methods for this highly ill-posed task operate in tightly …

To validate the second-by-second dynamics of turbines in field experiments, it is necessary
to accurately reconstruct the winds going into the turbine. Current time-resolved inflow …

Image restoration aims to recover high-quality images from degraded observations. When
the degradation process is known, the recovery problem can be formulated as an inverse …

Bayesian Optimal Experimental Design (BOED) is a powerful tool to reduce the cost of
running a sequence of experiments. When based on the Expected Information Gain (EIG) …

Diffusion bridges (DBs) are a class of diffusion models that enable faster sampling by
interpolating between two paired image distributions. Training traditional DBs for image …

Bayesian Optimal Experimental Design (BOED) is a powerful tool to reduce the cost of
running a sequence of experiments. When based on the Expected Information Gain (EIG) …

Diffusion models have emerged as powerful generative models for image synthesis, yet the
intricate relationship between input noise and generated images remains not fully …