Related papers: Analysis Framework for Multi-messenger Astronomy w…
Multi-view Multi-instance Multi-label Learning(M3L) deals with complex objects encompassing diverse instances, represented with different feature views, and annotated with multiple labels. Existing M3L solutions only partially explore the…
Punzo et al. (2015) recently reported on the state of the art for visualisation of H I data cubes. I here briefly describe another program, FRELLED, specifically designed for dealing with H I data. Unlike many 3D viewers, FRELLED can handle…
We search for a spatial association between radio pulsars and ultra-high energy neutrinos using the publicly available IceCube point source neutrino events catalog. For this purpose we use the unbinned maximum likelihood method to search…
Simulations with high accuracy are an essential part of scientific research to accelerate the innovation process. They are especially useful for finding novel approaches or optimizing existing methods. Today, powerful software tools are…
High-dimensional astronomical data cubes provide a wealth of spectral and structural information that can be used to study astrophysical and chemical processes. The complexity and sheer size of these datasets pose significant challenges in…
We outline a simple procedure designed for \emph{automatically} finding sets of multiple images in strong lensing (SL) clusters. We show that by combining (a) an arc-finding (or source extracting) program, (b) photometric redshift…
IceCube is a kilometer-scale high energy neutrino telescope under construction at the South Pole, a second-generation instrument expanding the capabilities of the AMANDA telescope. The scientific portfolio of IceCube includes the detection…
The sparsity-restricted maximum likelihood estimator (SMLE) has received considerable attention for feature screening in ultrahigh-dimensional regression. SMLE is a computationally convenient method that naturally incorporates the joint…
The association of two IceCube detections, the IceCube-170922A event and a neutrino flare, with the blazar TXS0506+056, has paved the way for the multimessenger quest for cosmic accelerators. IceCube has observed many other neutrinos but…
Triumvirate is a Python/C++ package for measuring the three-point clustering statistics in large-scale structure (LSS) cosmological analyses. Given a catalogue of discrete particles (such as galaxies) with their spatial coordinates, it…
We present a deep machine learning (ML) approach to constraining cosmological parameters with multi-wavelength observations of galaxy clusters. The ML approach has two components: an encoder that builds a compressed representation of each…
We introduce a framework for the use of large language models (LLMs) in Building Understandable Messaging for Policy and Evidence Review (BUMPER). LLMs are proving capable of providing interfaces for understanding and synthesizing large…
Quantifying differences between probability distributions is fundamental to statistics and machine learning, primarily for comparing statistical uncertainty. In contrast, epistemic uncertainty -- due to incomplete knowledge -- requires…
Forthcoming cosmic microwave background (CMB) polarized anisotropy experiments have the potential to revolutionize our understanding of the Universe and fundamental physics. The sought-after, tale-telling signatures will be however…
This paper deals with improving querying large language models (LLMs). It is well-known that without relevant contextual information, LLMs can provide poor quality responses or tend to hallucinate. Several initiatives have proposed…
This article presents a comparative study of three different types of estimators used for supervised linear unmixing of two MEx/OMEGA hyperspectral cubes. The algorithms take into account the constraints of the abundance fractions, in order…
The data from Cosmic Microwave Background (CMB) experiments are becoming more complex with each new experiment. A consistent way of analysing these data sets is required so that direct comparison is possible between the various experimental…
Machine learning (ML) models have significantly impacted various domains in our everyday lives. While large language models (LLMs) offer intuitive interfaces and versatility, task-specific ML models remain valuable for their efficiency and…
Kilometer-scale neutrino detectors such as IceCube are discovery instruments covering nuclear and particle physics, cosmology and astronomy. Examples of their multidisciplinary missions include the search for the particle nature of dark…
With the advent of a new generation of telescopes (INTEGRAL, Fermi, H.E.S.S., MAGIC, VERITAS, MILAGRO) and the prospects of planned observatories such as CTA or HAWC, gamma-ray astronomy is becoming an integral part of modern astrophysical…