Related papers: A Generative Modeling Approach to Reconstructing 2…
Coarse-graining (CG) of molecular simulations simplifies the particle representation by grouping selected atoms into pseudo-beads and drastically accelerates simulation. However, such CG procedure induces information losses, which makes…
Large-scale Fourier modes of the cosmic density field are of great value for learning about cosmology because of their well-understood relationship to fluctuations in the early universe. However, cosmic variance generally limits the…
Redshifted H{\sc\,i} 21 cm emission from unresolved low-redshift large scale structure is a promising window for ground-based Baryon Acoustic Oscillations (BAO) observations. A major challenge for this method is separating the cosmic signal…
The neutral hydrogen 21cm line is potentially a very powerful probe of the observable universe, and a number of on-going experiments are trying to detect it at cosmological distances. However, the presence of strong foreground radiations…
Studies of the cosmic dark ages ($30 \lesssim z \lesssim 150$) using the highly redshifted 21 cm line of neutral hydrogen offer unparalleled amounts of cosmological information, and recent years have seen the refinement of concepts for such…
The cosmic 21 cm signal is set to revolutionise our understanding of the early Universe, allowing us to probe the 3D temperature and ionisation structure of the intergalactic medium (IGM). It will open a window onto the unseen first…
A long-standing challenge in tomography is the 'missing wedge' problem, which arises when the acquisition of projection images within a certain angular range is restricted due to geometrical constraints. This incomplete dataset results in…
The sparse layouts of radio interferometers result in an incomplete sampling of the sky in Fourier space which leads to artifacts in the reconstructed images. Cleaning these systematic effects is essential for the scientific use of…
The 21-cm global signal is obscured by very bright galactic and extra galactic foreground emissions. Typical single-spectrum fit (SSF) based methods for foreground/signal separation can result in biased estimates of the cosmological signal…
Next-generation 21cm observations will enable imaging of reionization on very large scales. These images will contain more astrophysical and cosmological information than the power spectrum, and hence providing an alternative way to…
Deep learning models have significantly improved the visual quality and accuracy on compressive sensing recovery. In this paper, we propose an algorithm for signal reconstruction from compressed measurements with image priors captured by a…
The cosmological reionization can be studied in the radio through the tomographic view offered by the redshifted 21-cm line and the integrated information carried out by the diffuse free-free emission, coupled to the Comptonization…
Hippocampal subfield segmentation requires high-resolution T2w turbo spin echo (TSE) MRI, yet this sequence is susceptible to motion artifacts, leading to substantial data loss. We developed a conditional generative model (MRecover) that…
In this age of information, images are a critical medium for storing and transmitting information. With the rapid growth of image data amount, visual compression and visual data perception are two important research topics attracting a lot…
Ptychography is a well-studied phase imaging method that makes non-invasive imaging possible at a nanometer scale. It has developed into a mainstream technique with various applications across a range of areas such as material science or…
Due to the latest advances in technology, telescopes with significant sky coverage will produce millions of astronomical alerts per night that must be classified both rapidly and automatically. Currently, classification consists of…
Global (i.e. sky-averaged) $21$~cm signal experiments can measure the evolution of the universe from the Cosmic Dawn to the Epoch of Reionization. These measurements are challenged by the presence of bright foreground emission that can be…
Along with the prosperity of generative artificial intelligence (AI), its potential for solving conventional challenges in wireless communications has also surfaced. Inspired by this trend, we investigate the application of the advanced…
Reliable image transmission over wireless channels is particularly challenging at extremely low transmission rates, where conventional compression and channel coding schemes fail to preserve adequate visual quality. To address this issue,…
Building models capable of generating structured output is a key challenge for AI and robotics. While generative models have been explored on many types of data, little work has been done on synthesizing lidar scans, which play a key role…