Related papers: Introducing SESHAT: A Tool for Object Classificati…
I describe our team's development of the SpeX Prism Library Analysis Toolkit (SPLAT), a combined spectral data repository for over 2500 low-resolution spectra of very low mass dwarfs (late M, L and T dwarfs), and Python-based analysis…
In this paper, I present a new set of synthetic spectral energy distributions (SEDs) for young stellar objects (YSOs) spanning a wide range of evolutionary stages, from the youngest deeply embedded protostars to pre-main-sequence stars with…
The James Webb Space Telescope (JWST) is expected to revolutionize our understanding of the high-redshift Universe, and may be able to test the prediction that the first, chemically pristine (population III) stars formed with very high…
A significant portion of the data available today is found within tables. Therefore, it is necessary to use automated table extraction to obtain thorough results when data-mining. Today's popular state-of-the-art methods for table…
Photo-z algorithms that utilize SED template fitting have matured, and are widely adopted for use on high-redshift near-infrared data that provides a unique window into the early universe. Alternative photo-z methods have been developed,…
The first deep-field observations of the JWST have immediately yielded a surprisingly large number of very high redshift candidates, pushing the frontier of observability well beyond $z\gtrsim10$. We here present a detailed SED-fitting…
JWST has ushered in an era of unprecedented ability to characterize exoplanetary atmospheres. While there are over 5,000 confirmed planets, more than 4,000 TESS planet candidates are still unconfirmed and many of the best planets for…
Integral field spectroscopy (IFS) is a powerful tool for understanding the formation of galaxies across cosmic history. We present the observing strategy and first results of MSA-3D, a novel JWST program using multi-object spectroscopy in a…
The James Webb Space Telescope will allow to spectroscopically study an unprecedented number of galaxies deep into the reionization era, notably by detecting [OIII] and H$\beta$ nebular emission lines. To efficiently prepare such…
In this paper, we present a novel paradigm to enhance the ability of object detector, e.g., expanding categories or improving detection performance, by training on synthetic dataset generated from diffusion models. Specifically, we…
Unsupervised learning of low-dimensional, semantic representations of words and entities has recently gained attention. In this paper we describe the Semantic Entity Retrieval Toolkit (SERT) that provides implementations of our previously…
The Large Synoptic Survey Telescope (LSST) will be a ground-based, optical, all-sky, rapid cadence survey project with tremendous potential for discovering and characterizing asteroids. With LSST's large 6.5m diameter primary mirror, a wide…
Few-shot object detection~(FSOD), which aims to detect novel objects with limited annotated instances, has made significant progress in recent years. However, existing methods still suffer from biased representations, especially for novel…
Identifying stars belonging to different classes is vital in order to build up statistical samples of different phases and pathways of stellar evolution. In the era of surveys covering billions of stars, an automated method of identifying…
Object recognition has become a crucial part of machine learning and computer vision recently. The current approach to object recognition involves Deep Learning and uses Convolutional Neural Networks to learn the pixel patterns of the…
While recent Transformer-based approaches have shown impressive performances on event-based object detection tasks, their high computational costs still diminish the low power consumption advantage of event cameras. Image-based works…
Brown dwarfs are failed stars with very low mass (13 to 75 $M_J$), and an effective temperature lower than 2500 K. Thus, they play a key role in understanding the gap in the mass function between stars and planets. However, due to their…
Data fusion is a computational process widely used in Earth observation to generate high-resolution hyperspectral data cubes with two spatial and one spectral dimensions. It merges data from instruments with complementary characteristics:…
The critical first step in the search for life on exoplanets over the next decade is to determine whether rocky planets transiting small M-dwarf stars possess atmospheres and, if so, what processes sculpt them over time. Because of its…
We present synthetic observations for the first generations of galaxies in the Universe and make predictions for future deep field observations for redshifts greater than 6. Due to the strong impact of nebular emission lines and the…