These metals are supposed as Titanium. Detailed parameters of the acquisition geometry can be found in Table 1. This sample is 3D cone-beam data. The estimated spectrum is illustrated in Figure 1 ( Right). 2 2 Additional Details of Baselines In our experiments, we compare our proposed method against eight baseline MAR approaches. Specifically, it learns the prior distribution of metal-free CT images with a generative model in order to infer the lost sinogram in the metal-affected regions.

Camera-based physiological measurement is a fast growing field of computer vision.

Graph Collaborative Filtering (GCF) is widely used in personalized recommendation systems. However, GCF suffers from a fundamental problem where features tend to occupy the embedding space inefficiently (by spanning only a low-dimensional subspace).

Finally, PDE-Refiner's connection to diffusion models enables an accurate and efficient assessment of the model's predictive uncertainty, allowing us to estimate when the surrogate becomes inaccurate.

A widely discussed hypothesis regarding the cause of visual models' lack of robustness is that they can exploit human-imperceptible high-frequency components

We fully resolve the conjecture posed in Subramanian et al. (2022),