相关论文: From seagull to hummingbird: New diagnostic method…
Large-scale outflows driven by AGNs are an important element of galaxy evolution. Detailed analysis of their properties allows us to probe the activity history of the galactic nucleus and, potentially, other properties of the host galaxy. A…
Mergers are an important aspect of galaxy formation and evolution. We aim to test whether deep learning techniques can be used to reproduce visual classification of observations, physical classification of simulations and highlight any…
Keylogger detection involves monitoring for unusual system behaviors such as delays between typing and character display, analyzing network traffic patterns for data exfiltration. In this study, we provide a comprehensive analysis for…
The classification of galaxies as star forming or active is generally done in the ([O III]/Hbeta, [N II]/Halpha) plane. The Sloan Digital Sky Survey (SDSS) has revealed that, in this plane, the distribution of galaxies looks like the two…
We have developed a method for fast and accurate stellar population parameters determination in order to apply it to high resolution galaxy spectra. The method is based on an optimization technique that combines active learning with an…
Learning-based solutions for vision tasks require a large amount of labeled training data to ensure their performance and reliability. In single-task vision-based settings, inconsistency-based active learning has proven to be effective in…
The mechanisms that bring galaxies to strongly reduce their star formation activity (star-formation quenching) is still poorly understood. To better study galaxy evolution, we propose a classification based on the maps of the ionised…
Galaxy mergers and interactions have long been suggested as a significant driver of galaxy evolution. However, the exact extent to which mergers enhance star formation and AGN activity has been challenging to establish observationally. In…
We consider simple semi-analytic models that relate the active galactic nuclei (AGN) evolution to the merging history of their host dark matter haloes and quantify their ability of matching the AGN luminosity function and its spatial…
We study the spectral classification of emission-line galaxies as star-forming galaxies or Active Galactic Nuclei (AGNs). From the Sloan Digital Sky Survey (SDSS) high quality data, we define an improved classification to be used for high…
Graph Neural Networks (GNNs) for prediction tasks like node classification or edge prediction have received increasing attention in recent machine learning from graphically structured data. However, a large quantity of labeled graphs is…
The feedback from an active galactic nucleus (AGN) is frequently invoked as a mechanism through which gas can be heated or removed from a galaxy. However, gas fraction measurements in AGN hosts have yielded mixed support for this scenario.…
Learning behavioral taxonomies from animal-borne sensors is challenging because labels are scarce, classes are highly imbalanced, and behaviors may be absent from the annotated set. We study generalized behavior discovery in short…
We use 4 galaxies from the Calar Alto Legacy Integral Field Area (CALIFA) survey with clear signs of accretion onto supermassive black holes to investigate the relative contribution of star-formation and active galactic nucleus (AGN)…
Recent studies have shown that the choice of activation function can significantly affect the performance of deep learning networks. However, the benefits of novel activation functions have been inconsistent and task dependent, and…
Next generation interferometers, such as the Square Kilometre Array, are set to obtain vast quantities of information about the kinematics of cold gas in galaxies. Given the volume of data produced by such facilities astronomers will need…
Line intensity mapping is emerging as a novel method that can measure the collective intensity fluctuations of atomic/molecular line emission from distant galaxies. Several observational programs with various wavelengths are ongoing and…
We present analytical exploration of novel activation functions as consequence of integration of several ideas leading to implementation and subsequent use in habitability classification of exoplanets. Neural networks, although a powerful…
Cosmological hydrodynamical simulations are rich tools to understand the build-up of stellar mass and angular momentum in galaxies, but require some level of calibration to observations. We compare predictions at $z\sim0$ from the Eagle,…
In Liu (2015), we propose selecting binary active galactic nuclei (AGNs) candidates using the centroid shift of the images, which is induced by the non-synchronous variations of the two nuclei. In this paper, a known binary AGN (SDSS…