Related papers: Local Two-Sample Testing: A New Tool for Analysing…
Star formation is a multi-scale problem, and only global simulations that account for the connection from the molecular cloud scale gas flow to the accreting protostar can reflect the observed complexity of protostellar systems.…
This paper proposes a novel test method for high-dimensional mean testing regard for the temporal dependent data. Comparison to existing methods, we establish the asymptotic normality of the test statistic without relying on restrictive…
In this article, we develop and investigate a new classifier based on features extracted using spatial depth. Our construction is based on fitting a generalized additive model to the posterior probabilities of the different competing…
Environments play an important role in galaxy formation and evolution, particularly in regulating the content of neutral gas. However, current HI surveys have limitations in their depth, which prevents them from adequately studying low HI…
We present a new method that simultaneously solves for cosmology and galaxy bias on non-linear scales. The method uses the halo model to analytically describe the (non-linear) matter distribution, and the conditional luminosity function…
We introduce a low dimensional function of the site frequency spectrum that is tailor-made for distinguishing coalescent models with multiple mergers from Kingman coalescent models with population growth, and use this function to construct…
We review cosmological inference from galaxy surveys at low and high redshifts, with emphasis on new Southern sky surveys. We focus on several issues: (i) The importance of understanding selection effects in catalogues and matching Northern…
We report on our observing program to obtain integrated spectrophotometry, intermediate and high resolution major axis spectra, and U,B,R surface photo- metry of a representative sample of ~200 galaxies in the nearby field. The main goal of…
In high dimension, low sample size (HDLSS) settings, classifiers based on Euclidean distances like the nearest neighbor classifier and the average distance classifier perform quite poorly if differences between locations of the underlying…
Many recent works in simulation-based inference (SBI) rely on deep generative models to approximate complex, high-dimensional posterior distributions. However, evaluating whether or not these approximations can be trusted remains a…
The fraction of galaxies with red colours depends sensitively on environment, and on the way in which environment is measured. To distinguish competing theories for the quenching of star formation, a robust and complete description of…
We present a general framework for hypothesis testing on distributions of sets of individual examples. Sets may represent many common data sources such as groups of observations in time series, collections of words in text or a batch of…
We train graph neural networks to perform field-level likelihood-free inference using galaxy catalogs from state-of-the-art hydrodynamic simulations of the CAMELS project. Our models are rotational, translational, and permutation invariant…
In analyzing high-dimensional models, sparsity of the model parameter is a common but often undesirable assumption. In this paper, we study the following two-sample testing problem: given two samples generated by two high-dimensional linear…
A common problem in genetics is that of testing whether a set of highly dependent gene expressions differ between two populations, typically in a high-dimensional setting where the data dimension is larger than the sample size. Most…
The Chinese Space Station Optical Survey (CSS-OS) is a mission to explore the vast universe. This mission will equip a 2-meter space telescope to perform a multi-band NUV-optical large area survey (over 40% of the sky) and deep survey (~1%…
We present the results of a proof-of-concept experiment which demonstrates that deep learning can successfully be used for production-scale classification of compact star clusters detected in HST UV-optical imaging of nearby spiral galaxies…
This paper describes the systematic application of local topological methods for detecting interfaces and related anomalies in complicated high-dimensional data. By examining the topology of small regions around each point, one can…
Two-sample tests are important areas aiming to determine whether two collections of observations follow the same distribution or not. We propose two-sample tests based on integral probability metric (IPM) for high-dimensional samples…
We discuss the quantification of the local galaxy population and the impact of the ``New Era of Wide-Field Astronomy'' on this field, and, in particular, systematic errors in the measurement of the Luminosity Function. New results from the…