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In response to a recently reported observation of evidence for two classes of Type Ia Supernovae (SNe Ia) distinguished by their brightness in the rest-frame near ultraviolet (NUV), we search for the phenomenon in publicly available…

The properties of supernovae (SNe) are reviewed. It is shown that the observed characteristics of the morphological classes of SNe (types Ia, Ib/c, II) can be explained in terms of two basic explosion mechanisms, i.e. core collapse of…

Cosmological analyses of samples of photometrically-identified Type Ia supernovae (SNe Ia) depend on understanding the effects of 'contamination' from core-collapse and peculiar SN Ia events. We employ a rigorous analysis on…

Statistical pattern recognition methods have provided competitive solutions for variable star classification at a relatively low computational cost. In order to perform supervised classification, a set of features is proposed and used to…

The recognition and classification of the diversity of materials that exist in the environment around us are a key visual competence that computer vision systems focus on in recent years. Understanding the identification of materials in…

Classifying variable stars is crucial for advancing our understanding of stellar evolution and dynamics. As large-scale surveys generate increasing volumes of light curve data, the demand for automated and reliable classification techniques…

We present a novel method to produce empirical generative models of all kinds of astronomical transients from datasets of unlabeled light curves. Our hybrid model, that we call ParSNIP, uses a neural network to model the unknown intrinsic…

A new method to study the intrinsic color and luminosity of type Ia supernovae (SNe Ia) is presented. A metric space built using principal component analysis (PCA) on spectral series SNe Ia between -12.5 and +17.5 days from B maximum is…

We describe a search and classification procedure for gravitational waves emitted by core-collapse supernova (CCSN) explosions, using a convolutional neural network (CNN) combined with an event trigger generator known as Wavelet Detection…

This paper presents a deep learning approach to the classification of 160 shortwave radio signals. It addresses the typical challenges of the shortwave spectrum, which are the large number of different signal types, the presence of various…

Current synoptic sky surveys monitor large areas of the sky to find variable and transient astronomical sources. As the number of detections per night at a single telescope easily exceeds several thousand, current detection pipelines make…

We use three years of data from the Supernova Legacy Survey (SNLS) to study the general properties of core-collapse and type Ia supernovae. This is the first such study using the "rolling search" technique which guarantees well-sampled SNLS…

In the upcoming decade large astronomical surveys will discover millions of transients raising unprecedented data challenges in the process. Only the use of the machine learning algorithms can process such large data volumes. Most of the…

Both neural networks and decision trees are popular machine learning methods and are widely used to solve problems from diverse domains. These two classifiers are commonly used base classifiers in an ensemble framework. In this paper, we…

Astronomy light curves are sparse, gappy, and heteroscedastic. As a result standard time series methods regularly used for financial and similar datasets are of little help and astronomers are usually left to their own instruments and…

Future time-domain surveys for transient events in the near- and mid-infrared bands will significantly extend our understanding about the physics of the early Universe. In this paper we study the implications of a deep (~27 mag), long-term…

An understanding and classification of driving scenarios are important for testing and development of autonomous driving functionalities. Machine learning models are useful for scenario classification but most of them assume that data…

There is a growing demand for accurate high-resolution land cover maps in many fields, e.g., in land-use planning and biodiversity conservation. Developing such maps has been performed using Object-Based Image Analysis (OBIA) methods, which…

Theoretical and observational cosmology have enjoyed a number of significant successes over the last two decades. Cosmic microwave background measurements from the Wilkinson Microwave Anisotropy Probe and Planck, together with large-scale…

Core-collapse supernovae (CCSNe) are powerful sources of gravitational waves (GWs). These signals propagate essentially unobstructed, providing a unique probe of the supernova central engine. In this work, we investigate parameter…