相关论文: Classification of Fermi-LAT unidentified gamma-ray…

We present the results of our follow-up observation program of gamma-ray sources detected by the Large Area Telescope (LAT) on board the Fermi Gamma-ray Space Telescope. 26 blazars and 39 sources unidentified at other wavelengths were…

The work in ICML'09 showed that the derivatives of the classical multi-class logistic regression loss function could be re-written in terms of a pre-chosen "base class" and applied the new derivatives in the popular boosting framework. In…

Aims. We aim here to contribute to the identification of unassociated bright sources of gamma-rays in the recently released catalogue obtained by the Fermi collaboration. Methods. Our work is based on a extensive cross-identification of…

With a decade of gamma-ray data from the Fermi-LAT telescope, we can now hope to answer how well we know the local Universe at gamma-ray frequencies. On the other hand, with gamma-ray data alone it is not possible to directly access the…

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:…

We present a catalog of high-energy gamma-ray sources detected by the Large Area Telescope (LAT), the primary science instrument on the Fermi Gamma-ray Space Telescope (Fermi), during the first 11 months of the science phase of the mission,…

Large fraction of studies of active galactic nuclei objects is based on performing follow-up observations using high-sensitivity instruments of high flux states observed by monitoring instruments (the so-called Target of Opportunity, ToO).…

The first three months of sky-survey operation with the Fermi Gamma Ray Space Telescope (Fermi) Large Area Telescope (LAT) reveals 132 bright sources at |b|>10 deg with test statistic greater than 100 (corresponding to about 10 sigma). Two…

Blazars are the most common sources of $\gamma$-ray photons in the extragalactic sky. Their $\gamma$-ray light curves are characterized by bright flaring episodes, similarly to what is observed at longer wavelengths. These gamma-ray bursts…

Uplift modeling comprises a collection of machine learning techniques designed for managers to predict the incremental impact of specific actions on customer outcomes. However, accurately estimating this incremental impact poses significant…

Fraud detection remains a critical task in high-stakes domains such as finance and e-commerce, where undetected fraudulent transactions can lead to significant economic losses. In this study, we systematically compare the performance of…

Gradient boosting machines (GBMs) based on decision trees consistently demonstrate state-of-the-art results on regression and classification tasks with tabular data, often outperforming deep neural networks. However, these models do not…

As data collections become larger, exploratory regression analysis becomes more important but more challenging. When observations are hierarchically clustered the problem is even more challenging because model selection with mixed effect…

With assistance of the identified/associated sources in the second Fermi Large Area Telescope (LAT) catalog, we analyze and resolve the spatial distribution and the distributions of the gamma-ray spectral and variability indices of the…

We present the first Fermi Large Area Telescope (LAT) catalog of long-term $\gamma$-ray transient sources (1FLT). This comprises sources that were detected on monthly time intervals during the first decade of Fermi-LAT operations. The…

Nearly one-third of the sources in the $Fermi$-LAT catalogs lack a lower energy counterpart, hence being referred as unidentified/unassociated gamma-ray sources (UGSs). In order to firmly classify them, dedicated multifrequency follow-up…

Despite the success of deep learning in computer vision and natural language processing, Gradient Boosted Decision Tree (GBDT) is yet one of the most powerful tools for applications with tabular data such as e-commerce and FinTech. However,…

Breast-Conserving Surgery (BCS) requires precise intraoperative margin assessment to preserve healthy tissue. Deep Ultraviolet Fluorescence Scanning Microscopy (DUV-FSM) offers rapid, high-resolution surface imaging for this purpose;…

Gradient tree boosting is a prediction algorithm that sequentially produces a model in the form of linear combinations of decision trees, by solving an infinite-dimensional optimization problem. We combine gradient boosting and Nesterov's…

The Fermi Large Area Telescope (LAT) Collaboration has recently released the Third Catalog of Hard Fermi-LAT Sources (3FHL), which contains 1556 sources detected above 10 GeV with seven years of Pass 8 data. We investigate the source count…