Related papers: The first AKRA mass map reconstruction from HSC Y1…

We study the accuracy with which weak lensing measurements could be made from a future space-based survey, predicting the subsequent precisions of 3-dimensional dark matter maps, projected 2-dimensional dark matter maps, and mass-selected…

We present new wide-field weak lensing mass maps for the Year 1 Dark Energy Survey data, generated via a forward fitting approach. This method of producing maps does not impose any prior constraints on the mass distribution to be…

Weak lensing will play an important role in future cosmological surveys, including e.g. Euclid and SKA. Sufficiently accurate theoretical predictions are important for correctly interpreting these surveys and hence for extracting correct…

Extending previous studies, we derive generic predictions for lower order cumulants and their correlators for individual tomographic bins as well as between two different bins. We derive the corresponding one- and two-point joint…

Most high-dimensional matrix recovery problems are studied under the assumption that the target matrix has certain intrinsic structures. For image data related matrix recovery problems, approximate low-rankness and smoothness are the two…

We describe a weak lensing view of the downsizing of star forming galaxies based on cross correlating a weak lensing ($\kappa$) map with a predicted map constructed from a redshift survey. Moderately deep and high resolution images with…

We present a novel, model-independent technique for fitting the cross-component of weak lensing shear, $\gamma_\times$, along a line of sight by combining kinematic and photometric measurements of a single lensed galaxy. Rather than relying…

We describe a novel end-to-end approach using Machine Learning to reconstruct the power spectrum of cosmological density perturbations at high redshift from observed quasar spectra. State-of-the-art cosmological simulations of structure…

We develop a new efficient sequential approximate leverage score algorithm, SALSA, using methods from randomized numerical linear algebra (RandNLA) for large matrices. We demonstrate that, with high probability, the accuracy of SALSA's…

The high sensitivity of the new generation of radio telescopes such as the Square Kilometre Array (SKA) will allow cosmological weak lensing measurements at radio wavelengths that are competitive with optical surveys. We present an…

Retrieval augmented generation (RAG) has transformed text based question answering, yet its extension to visual domains remains hindered by fundamental challenges: bridging the modality gap between image queries and text heavy knowledge…

We present a joint cosmological analysis of the two-point correlation function and the aperture-mass skewness measured from the Year 3 data of the Hyper Suprime-Cam Subaru Strategic Program (HSC-Y3). The aperture-mass skewness is a…

Robust principal component analysis (RPCA) can recover low-rank matrices when they are corrupted by sparse noises. In practice, many matrices are, however, of high-rank and hence cannot be recovered by RPCA. We propose a novel method called…

Metal implants in MRI cause severe artifacts that degrade image quality and hinder clinical diagnosis. Traditional approaches address metal artifact reduction (MAR) and accelerated MRI acquisition as separate problems. We propose MASC, a…

We propose and evaluate a new MRI reconstruction method named LORAKI that trains an autocalibrated scan-specific recurrent neural network (RNN) to recover missing k-space data. Methods like GRAPPA, SPIRiT, and AC-LORAKS assume that k-space…

The measurement of cosmic shear using weak gravitational lensing is a challenging task that involves a number of complicated procedures. We study in detail the systematic errors in the measurement of weak lensing Minkowski Functionals…

The low-rank matrix approximation problem with respect to the component-wise $\ell_1$-norm ($\ell_1$-LRA), which is closely related to robust principal component analysis (PCA), has become a very popular tool in data mining and machine…

We perform a cosmic shear analysis in harmonic space using the first year of data collected by the Dark Energy Survey (DES-Y1). We measure the cosmic weak lensing shear power spectra using the Metacalibration catalogue and perform a…

The widely used MASTER approach for angular power spectrum estimation was developed as a fast $C_{\ell}$ estimator on limited regions of the sky. This method expresses the power spectrum of a masked map ("pseudo-$C_\ell$") in terms of the…

The majority of existing hyperspectral anomaly detection (HAD) methods use the low-rank representation (LRR) model to separate the background and anomaly components, where the anomaly component is optimized by handcrafted sparse priors…