To enhance low-light images to normally-exposed ones is highly ill-posed, namely that the mapping relationship between them one-to-many. Previous works based on pixel-wise reconstruction losses and deterministic processes fail capture complex conditional distribution of normally exposed images, which results in improper brightness, residual noise, artifacts. In this paper, we investigate model ...

In Bayesian inference, a Bayes factor is deened as the ratio of posterior odds versus prior odds where posterior odds is simply a ratio of the normalizing constants of two posterior densities. In many practical problems, the two posteriors have diierent dimensions. For such cases, the current Monte Carlo methods such as the bridge sampling method (Meng and Wong 1996), the path sampling method (...

In the process of three-dimensional reconstruction of single particle biological macromolecules several hundreds, or thousands, of projection images are taken from tens or hundreds of independently digitized micrographs. These different micrographs show differences in the background grey level and particle contrast and, therefore, have to be normalized by scaling their pixel values before enter...

The desire to be more responsive the demands of citizens complicates relationship between Secretary State and Permanent has an impact on policy delivery capacity. This article considers four separate contributions effective in a context increasing increasingly variegated demands: those provided by State, Secretary, special political adviser (SpAd) chair departmental board. Drawing insights garn...

Abstract Movement models predict positions of players (or objects in general) over time and are thus key to analyzing spatiotemporal data as it is often used sports analytics. Existing movement either designed from physical principles or entirely data-driven. However, the former suffers oversimplifications achieve feasible interpretable models, while latter relies on computationally costly, a c...

This paper introduces an end-to-end learned image compression system, termed ANFIC, based on Augmented Normalizing Flows (ANF). ANF is a new type of flow model, which stacks multiple variational autoencoders (VAE) for greater model expressiveness. The VAE-based has gone mainstream, showing promising performance. Our work presents the first attempt to leverage in flow-based framework. ANFIC adva...