Related papers: AstroPT: Scaling Large Observation Models for Astr…

This work addresses the challenge of training supervised machine or deep learning models on orbiting platforms where we are generally constrained by limited on-board hardware capabilities and restricted uplink bandwidths to upload. We aim…

In this work, we introduce an innovative autoregressive model leveraging Generative Pretrained Transformer (GPT) architectures, tailored for fraud detection in payment systems. Our approach innovatively confronts token explosion and…

Large Language Models (LLMs) are shifting how scientific research is done. It is imperative to understand how researchers interact with these models and how scientific sub-communities like astronomy might benefit from them. However, there…

This study is devoted to the cosmological "angular size - redshift" test. An analysis is performed of the angular and linear sizes of galaxies from the new ASTRODEEP-JWST catalogue, which contains over 500,000 objects at high redshifts (up…

Large pre-trained models have demonstrated remarkable capabilities across domains, but their effectiveness in time series forecasting remains understudied. This work empirically examines whether pre-trained large-scale time series models…

ASTROSAT is an astronomy satellite designed for simultaneous multi-wavelength studies in the Optical/UV and a broad X-ray energy range. With four X-ray instruments and a pair of UV-Optical telescopes, ASTROSAT will provide unprecendented…

The highly successful SuperWASP planetary transit finding programme has surveyed a large fraction of both the northern and southern skies. There now exists in the its archive over 420 billion photometric measurements for more than 31…

Vacuum birefringence from Lorentz and CPT violation in the Standard-Model Extension can be constrained using ground-based optical polarimetry of extragalactic sources. We describe results from a pilot program with an automated system that…

Obtaining pulsar parallaxes via relative astrometry (also known as differential astrometry) yields distances and transverse velocities that can be used to probe properties of the pulsar population and the interstellar medium. Large programs…

Large-scale pre-trained models (PTMs) such as BERT and GPT have recently achieved great success in Natural Language Processing and Computer Vision domains. However, the development of PTMs on healthcare time-series data is lagging…

The accuracy of astrometric observations conducted via a space-borne optical interferometer orbiting the Earth is expected to approach a few microarcseconds. Data processing of such extremely high-precision measurements requires access to a…

Optical polarimetry provides information on the geometry of the emitting region, the magnetic field configuration and the properties of dust in astrophysical sources. Current state-of-the-art instruments typically have a small field of view…

The NASA Astrophysics Data System (ADS) is an essential tool for researchers that allows them to explore the astronomy and astrophysics scientific literature, but it has yet to exploit recent advances in natural language processing. At…

In recent years, autoregressive models have had a profound impact on the description of astronomical time series as the observation of a stochastic process. These methods have advantages compared with common Fourier techniques concerning…

Earth observation is becoming one of the largest data-producing activities in science, yet current pipelines still treat compression as a storage and transmission tool rather than a new way to use data. We present a generative compression…

Observational astronomy has undergone a significant transformation driven by large-scale surveys, such as the Panoramic Survey Telescope and Rapid Response System (Pan-STARRS) Survey, the Sloan Digital Sky Survey (SDSS), and the Gaia…

Look-Up Table based methods have emerged as a promising direction for efficient image restoration tasks. Recent LUT-based methods focus on improving their performance by expanding the receptive field. However, they inevitably introduce…

The ongoing optical time-domain astronomy surveys are routinely reporting fifty transient candidates per night. Here, I investigate the demographics of astronomical transients and supernova classifications reported to the Transient Name…

Pretrained foundation models and transformer architectures have driven the success of large language models (LLMs) and other modern AI breakthroughs. However, similar advancements in health data modeling remain limited due to the need for…

The Advanced Technology Large Aperture Space Telescope (ATLAST) is a set of mission concepts for the next generation UV-Optical-Near Infrared space telescope with an aperture size of 8 to 16 meters. ATLAST, using an internal coronagraph or…