相关论文: Constraining Photoionization Models With a Reproje…
A Generative Adversarial Network (GAN) with generator $G$ trained to model the prior of images has been shown to perform better than sparsity-based regularizers in ill-posed inverse problems. Here, we propose a new method of deploying a…
Kiloparsec-scale binary active galactic nuclei (AGNs) signal active supermassive black hole (SMBH) pairs in merging galaxies. Despite their significance, unambiguously confirmed cases remain scarce and most have been discovered…
Narrow emission-line galaxies can be distinguished in the well-known BPT diagrams through narrow emission line properties. However, there are no boundaries visible to the naked eye between type-2 AGN and HII galaxies in BPT diagrams,…
In radio astronomy obtaining a high dynamic range in synthesis imaging of wide fields requires a correction for time and direction-dependent effects. Applying direction-dependent correction can be done by either partitioning the image in…
We present BOND, a Bayesian code to simultaneously derive oxygen and nitrogen abundances in giant H II regions. It compares observed emission lines to a grid of photoionization models without assuming any relation between O/H and N/O. Our…
Phase imaging in electron microscopy is sensitive to the local potential, including charge redistribution from bonding. We demonstrate that electron ptychography provides the necessary sensitivity to detect this subtle effect by directly…
We present a new scheme for modeling the broad line region in active galactic nuclei (AGNs). It involves photoionization calculations of a large number of clouds, in several pre-determined geometries, and a comparison of the calculated line…
To explain the properties of the local galaxy population, theoretical models require active galactic nuclei (AGN) to inject energy into host galaxies, thereby expelling outflows of gas that would otherwise form stars. Observational tests of…
While medical image segmentation is an important task for computer aided diagnosis, the high expertise requirement for pixelwise manual annotations makes it a challenging and time consuming task. Since conventional data augmentations do not…
Contamination from stars in the galaxy samples of large-scale structure surveys can bias cosmological constraints if not tightly controlled. This is especially true for lens samples used for galaxy clustering and galaxy-galaxy lensing…
Optical emission line diagnostics, which are a common tool to constrain the properties of the interstellar medium (ISM) of galaxies, become progressively inaccessible at higher redshifts for ground-based facilities. Far-infrared (FIR)…
We present a new Bayesian non-parametric deprojection algorithm DOPING (Deprojection of Observed Photometry using and INverse Gambit), that is designed to extract 3-D luminosity density distributions $\rho$ from observed surface brightness…
When developing clinical prediction models, it can be challenging to balance between global models that are valid for all patients and personalized models tailored to individuals or potentially unknown subgroups. To aid such decisions, we…
The identification of $\gamma$-rays from the predominant hadronic-background is a key aspect in their ground-based detection using Imaging Atmospheric Cherenkov Telescopes (IACTs). While current methods are limited in their ability to…
Aims: we seek to provide additional tests of the line formation of theoretical 3D solar photosphere models. In particular, we set out to test the spatially-resolved line formation at several viewing angles, from the solar disk-centre to the…
The open-world test dataset is often mixed with out-of-distribution (OOD) samples, where the deployed models will struggle to make accurate predictions. Traditional detection methods need to trade off OOD detection and in-distribution (ID)…
Convolutional neural networks (CNNs) show impressive performance for image classification and detection, extending heavily to the medical image domain. Nevertheless, medical experts are sceptical in these predictions as the nonlinear…
Emission line spectra from HII regions are often used to study properties of the gas in star-forming regions, as well as temperatures and luminosities of the ionising sources. Empirical diagnostics for the interpretation of observational…
For early diagnosis of malignancies in the gastrointestinal tract, surveillance endoscopy is increasingly used to monitor abnormal tissue changes in serial examinations of the same patient. Despite successes with optical biopsy for in vivo…
Interpretability is crucial to enhance trust in machine learning models for medical diagnostics. However, most state-of-the-art image classifiers based on neural networks are not interpretable. As a result, clinicians often resort to known…