Related papers: Machine learning-assisted techniques for Compton-b…

We report on an hybrid in-beam PET and prompt-gamma Compton imaging system aimed at quasi real-time ion-range verification in proton-therapy treatments. Proof-of-concept experiments were carried out at the radiobiology beam line of the CNA…

Acquiring labels are often costly, whereas unlabeled data are usually easy to obtain in modern machine learning applications. Semi-supervised learning provides a principled machine learning framework to address such situations, and has been…

The ensemble Gaussian mixture filter (EnGMF) is a non-linear filter suited to data assimilation of highly non-Gaussian and non-linear models that has practical utility in the case of a small number of samples, and theoretical convergence to…

Gaussian processes (GPs) have been extensively utilized as nonparametric models for component separation in 21 cm data analyses. This exploits the distinct spectral behavior of the cosmological and foreground signals, which are modeled…

This paper considers the problem of networks reconstruction from heterogeneous data using a Gaussian Graphical Mixture Model (GGMM). It is well known that parameter estimation in this context is challenging due to large numbers of variables…

We demonstrate the use of a convolutional neural network to perform neutron-gamma pulse shape discrimination, where the only inputs to the network are the raw digitised SiPM signals from a dual scintillator detector element made of…

Machine learning (ML) techniques have been demonstrated to improve the accuracy and efficiency of anomaly detection (AD) when compared to conventional methods. This has led to the adoption of ML for data quality monitoring (DQM) use cases…

We develop a framework to establish benchmarks for machine learning and deep neural networks analyses of exclusive scattering cross sections (FemtoNet). Within this framework we present an extraction of Compton form factors for deeply…

The neutrons emitted in heavy-ion fusion-evaporation (HIFE) reactions together with the gamma-rays cause unwanted backgrounds in gamma-ray spectra. Especially in the nuclear reactions, where relativistic ion beams (RIBs) are used, these…

GRETA, the Gamma-Ray Energy Tracking Array, is an array of highly-segmented HPGe detectors designed to track {\gamma}-rays emitted in beam-physics experiments. Its high detection efficiency and state-of-the-art position resolution make it…

A fast forward feature selection algorithm is presented in this paper. It is based on a Gaussian mixture model (GMM) classifier. GMM are used for classifying hyperspectral images. The algorithm selects iteratively spectral features that…

Multimodal learning integrates diverse modalities but suffers from modality imbalance, where dominant modalities suppress weaker ones due to inconsistent convergence rates. Existing methods predominantly rely on static modulation or…

The Compressed Baryonic Matter (CBM) experiment is a part of the Facility for Antiproton and Ion Research (FAIR) in Darmstadt at the GSI. The CBM experiment will investigate the highly compressed nuclear matter using nucleus-nucleus…

We present a maximum likelihood (ML) algorithm that is fast enough to detect gamma-ray transients in real time on low-performance processors often used for space applications. We validate the routine with simulations and find that, relative…

Gaussian processes (GP) for machine learning have been studied systematically over the past two decades and they are by now widely used in a number of diverse applications. However, GP kernel design and the associated hyper-parameter…

We investigate a Gaussian mixture model (GMM) with component means constrained in a pre-selected subspace. Applications to classification and clustering are explored. An EM-type estimation algorithm is derived. We prove that the subspace…

Gaseous PhotoMultipliers (GPM) are a very promising alternative of vacuum PMTs especially for large-size noble-liquid detectors in the field of Functional Nuclear Medical Imaging and Direct Dark Matter Detection. We present recent…

The next generation of radioactive ion beam facilities, which will give experimental access to many exotic nuclei, are presently being developed. At the same time the next generation of high resolution gamma-ray spectrometers, based on…

We apply the matrix element method (MEM) to the search for non-resonant Higgs boson pair ($\textrm{HH}$) production in the channel $\textrm{HH} \to \textrm{b}\bar{\textrm{b}}\textrm{W}\textrm{W}^{*}$ at the LHC and study the separation…

Sourceless efficiency calibration of high-purity germanium (HPGe) detectors can provide accurate detector-response information without experiments using radioactive calibration sources, offering advantages in both convenience and safety. In…