相关论文: Denoising Milky Way stellar survey data with norma…

The stellar velocity distribution function (DF) in the solar vicinity is re-examined using data from the SDSS APOGEE survey's DR16 and \emph{Gaia} DR2. By exploiting APOGEE's ability to chemically discriminate with great reliability the…

High-speed quantitative phase imaging enables non-intrusive visualization of transient compressible gas flows and energetic phenomena. However, phase maps reconstructed via the transport of intensity equation (TIE) suffer from spatially…

We present a non-parametric model for inferring the three-dimensional (3D) distribution of dust density in the Milky Way. Our approach uses the extinction measured towards stars at different locations in the Galaxy at approximately known…

Hypervelocity stars (HVSs) are amongst the fastest objects in our Milky Way. These stars are predicted to come from the Galactic center (GC) and travel along unbound orbits across the Galaxy. In the coming years, the ESA satellite Gaia will…

Normalizing Flows (NFs) are universal density estimators based on Neural Networks. However, this universality is limited: the density's support needs to be diffeomorphic to a Euclidean space. In this paper, we propose a novel method to…

To capture individual gait patterns, excluding identity-irrelevant cues in walking videos, such as clothing texture and color, remains a persistent challenge for vision-based gait recognition. Traditional silhouette- and pose-based methods,…

The Gaia mission has provided the largest ever astrometric chart of the Milky Way. Using it to map the Galactic halo is helpful for disentangling its merger history. The identification of halo stars in Gaia DR2 with reliable distance…

We present a novel generative modeling method called diffusion normalizing flow based on stochastic differential equations (SDEs). The algorithm consists of two neural SDEs: a forward SDE that gradually adds noise to the data to transform…

The growing trove of precision astrometric observations from the Gaia space telescope and other surveys is revealing the structure and dynamics of the Milky Way in ever more exquisite detail. We summarize the current status of our…

Optimal extraction of cosmological information from observations of the Cosmic Microwave Background critically relies on our ability to accurately undo the distortions caused by weak gravitational lensing. In this work, we demonstrate the…

We present an atlas and follow-up spectroscopic observations of 87 thin stream-like structures detected with the STREAMFINDER algorithm in Gaia DR3, of which 29 are new discoveries. Here we focus on using these streams to refine mass models…

Gaussian denoising has emerged as a powerful method for constructing simulation-free continuous normalizing flows for generative modeling. Despite their empirical successes, theoretical properties of these flows and the regularizing effect…

Astrometry from space has unique advantages over ground-based observations: the all-sky coverage, relatively stable, and temperature and gravity invariant operating environment delivers precision, accuracy and sample volume several orders…

In supervised learning for image denoising, usually the paired clean images and noisy images are collected or synthesised to train a denoising model. L2 norm loss or other distance functions are used as the objective function for training.…

We develop a framework for modelling the Milky Way using stellar streams and a wide range of photometric and kinematic observations. Through the use of mock data we demonstrate that a standard suite of Galactic observations leads to…

The census of stellar streams and dwarf galaxies in the Milky Way provides direct constraints on galaxy formation models and the nature of dark matter. The DESI Milky Way survey (with a footprint of 14,000$~deg{^2}$ and a depth of $r<19$…

We develop a new machine learning algorithm, Via Machinae, to identify cold stellar streams in data from the Gaia telescope. Via Machinae is based on ANODE, a general method that uses conditional density estimation and sideband…

The Gaia mission has led to the discovery of over 100 stellar streams in the Milky Way, most of which likely originated from globular clusters (GCs). As the upcoming wide-field surveys can potentially continue to increase the number of…

In this study, we proposed an efficient approach based on a deep learning (DL) denoising autoencoder (DAE) model for denoising noisy flow fields. The DAE operates on a self-learning principle and does not require clean data as training…

Denoising has always been theoretically considered as removal of high frequency disturbances having Gaussian distribution. Here we relax this assumption and the method used here is completely different from traditional thresholding schemes.…