Related papers: Periodicity detection in AGN with the boosted tree…

Fifteen ROSAT PSPC observations available in the public archive are analyzed in order to study time and spectral variability of the 12 EMSS AGN detected by ROSAT with more than 2000 net counts. Time variability was investigated on 13…

We have searched quasi-periodic oscillations (QPOs) for BL Lac PKS J2134-0153 in the 15 GHz radio light curve announced by the Owens Valley Radio Observatory 40-m telescope during the period from 2008-01-05 to 2019-05-18, utilizing the…

The absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties are important in drug discovery as they define efficacy and safety. In this work, we applied an ensemble of features, including fingerprints and…

The search for periodicity in the multi-wavelength high variable emission of blazars is a key feature to understand dynamical processes at work in this class of active galactic nuclei. The blazar PG 1553+113 is an attractive target due to…

The search for radio signals from exoplanets or star-planet interactions is a topic of major scientific interest, as it is likely the best way to detect and measure a planetary magnetic field and, therefore, to probe the inner structure of…

The statistical properties of energy and waiting time carry essential information about the source of repeating fast radio bursts (FRBs). In this paper, we investigate the randomness of energy and waiting time using four data samples from…

In this paper we propose a novel machine-learning method for anomaly detection applicable to data with periodic characteristics where randomly varying period lengths are explicitly allowed. A multi-dimensional time series analysis is…

Context: Periodicity in 6.7 GHz methanol maser sources is a rare phenomenon that was discovered during long-term monitoring programmes. Understanding the underlying processes that lead to periodic variability might provide insights into the…

Optical variability has proven to be an effective way of detecting AGNs in imaging surveys, lasting from weeks to years. In the present work we test its use as a tool to identify AGNs in the VST multi-epoch survey of the COSMOS field,…

Context: The gamma-ray binary LSI+61303 shows multiple periodicities. The timing analysis of 6.7 yr of GBI radio data and of 6 yr of Fermi-LAT GeV gamma-ray data both have found two close periodicities P1(GBI) = 26.49 \pm 0.07 d,…

Machine learning algorithms such as random forests or xgboost are gaining more importance and are increasingly incorporated into production processes in order to enable comprehensive digitization and, if possible, automation of processes.…

We present XMM-Newton observations of a complete sample of five archetypal young radio-loud AGN, also known Gigahertz Peaked Spectrum (GPS) sources. They are among the brightest and best studied GPS/CSO sources in the sky, with radio powers…

In biostatistics, propensity score is a common approach to analyze the imbalance of covariate and process confounding covariates to eliminate differences between groups. While there are an abundant amount of methods to compute propensity…

While the space of renewable energy forecasting has received significant attention in the last decade, literature has primarily focused on machine learning models that train on only one objective at a time. A host of classification (and…

State-of-the-art implementations of boosting, such as XGBoost and LightGBM, can process large training sets extremely fast. However, this performance requires that the memory size is sufficient to hold a 2-3 multiple of the training set…

This paper proposes a hybrid framework combining LSTM (Long Short-Term Memory) networks with LightGBM and CatBoost for stock price prediction. The framework processes time-series financial data and evaluates performance using seven models:…

The policy environment of countries changes rapidly, influencing macro-level indicators such as the Energy Security Index. However, this index is only reported annually, limiting its responsiveness to short-term fluctuations. To address…

This work explores the use of gradient boosting in the context of classification. Four popular implementations, including original GBM algorithm and selected state-of-the-art gradient boosting frameworks (i.e. XGBoost, LightGBM and…

In this letter we present the results of a wavelet analysis of the radio light curve of the BL Lac Object PKS B0048-097 from the University of Michigan Radio Astronomy Observatory monitoring program at 8GHz during twenty-five years, from…

This study evaluates the performance of various supervised machine learning models in analyzing highly correlated neural signaling data from the Adolescent Brain Cognitive Development (ABCD) Study, with a focus on predicting…