Related papers: Reconstructing the Position and Intensity of Multi…

Discovered after the end of the Compton Gamma-Ray Observatory mission, the radio pulsar PSR J2021+3651 was long considered a likely counterpart of the high-energy gamma-ray source 2CG 075+00 = 3EG J2021+3716 = GeV J2020+3658, but it could…

Because of the relatively broad angular resolution of current gamma-ray instruments in the MeV-GeV energy range, the photons of a given source are mixed with those coming from nearby sources or diffuse background. This source confusion…

Aims. We present the second AGILE-GRID Catalog (2AGL) of {\gamma}-ray sources in the 100 MeV-10 GeV energy range. Methods. With respect to previous AGILE-GRID catalogs, the current 2AGL Catalog is based on the first 2.3 years of science…

We demonstrate a method for using arrays of point sources that emulate -- when measured from a standoff of at least several meters -- distributed gamma-ray sources, and present results using this method from outdoor aerial measurements of…

We propose a new algorithm to learn the network of the interactions of pairwise Ising models. The algorithm is based on the pseudo-likelihood method (PLM), that has already been proven to efficiently solve the problem in a large variety of…

We present a novel Simultaneous Localization and Mapping (SLAM) method that employs Gaussian Process (GP) based landmark (object) representations. Instead of conventional grid maps or point cloud registration, we model the environment on a…

We have developed an image restoration technique based on the Richardson-Lucy algorithm optimized for GLAST-LAT image analysis. Our algorithm is original since it utilizes the PSF (point spread function) that is calculated for each event.…

It is challenging to recover the large-scale internet traffic data purely from the link measurements. With the rapid growth of the problem scale, it will be extremely difficult to sustain the recovery accuracy and the computational cost. In…

The Large Area Telescope (LAT) on board the \emph{Fermi} Gamma-ray Space Telescope has been continuously providing good quality survey data of the entire sky in the high energy range from 30 MeV to 500 GeV and above since August 2008. A…

Airborne Laser Scanning (ALS) can collect point clouds across large areas, enabling large-scale forest inventory. However, ALS point clouds are sparse and noisy, resulting in inaccurate individual-tree-level forest inventory, such as stem…

We propose a new point-spread function (PSF) deconvolution algorithm for images of galaxies hosting an active galactic nucleus (AGN), designed to simultaneously enhance the spatial resolution of the host galaxy and remove the bright central…

At GeV energies, the sky is dominated by the interstellar emission from the Galaxy. With limited statistics and spatial resolution, accurately separating point sources is therefore challenging. Here we present the first application of deep…

The Segment Anything Model (SAM) has demonstrated strong performance in image segmentation of natural scene images. However, its effectiveness diminishes markedly when applied to specific scientific domains, such as Scanning Probe…

Image Phase Alignment Super-sampling (ImPASS) is a computational method for combining displaced low-resolution images into a single high-resolution image. The general steps include measuring the relative displacements, up-sampling, aligning…

With the advent of wide-area submillimeter surveys, a large number of high-redshift gravitationally lensed dusty star-forming galaxies (DSFGs) has been revealed. Due to the simplicity of the selection criteria for candidate lensed sources…

This paper proposes a new sparse array source enumeration algorithm for underdetermined scenarios with more sources than sensors. The proposed algorithm decomposes the wideband signals into multiple uncorrelated frequency bands, computes…

Unsupervised anomaly detection aims to build models to effectively detect unseen anomalies by only training on the normal data. Although previous reconstruction-based methods have made fruitful progress, their generalization ability is…

Precise localisation of gamma-ray interactions is crucial for the performance of the Advanced GAmma Tracking Array (AGATA). The Pulse Shape Analysis (PSA) method used for the position estimation of gamma-ray interactions relies on a…

Training deep learning models for point cloud prediction tasks such as shape completion and generation depends critically on loss functions that measure discrepancies between predicted and ground-truth point sets. Commonly used functions…

Generation of simulated data is essential for data analysis in particle physics, but current Monte Carlo methods are very computationally expensive. Deep-learning-based generative models have successfully generated simulated data at lower…