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The environmental impacts of global warming driven by methane (CH4) emissions have catalyzed significant research initiatives in developing novel technologies that enable proactive and rapid detection of CH4. Several data-driven machine…
High-Purity Germanium (HPGe) detectors are a key technology for rare-event searches such as neutrinoless double-beta decay (\ensuremath{0\nu\beta\beta}) and dark matter experiments. Pulse shapes from these detectors vary with interaction…
To develop a machine learning-based framework for accurately modeling the anode heel effect in Monte Carlo simulations of X-ray imaging systems, enabling realistic beam intensity profiles with minimal experimental calibration. Multiple…
In modern wireless communication systems, radio propagation modeling to estimate pathloss has always been a fundamental task in system design and optimization. The state-of-the-art empirical propagation models are based on measurements in…
``Oversimplified'' and ``simplified'' methods based on true coincidence summing effect used in uncomplicated determination of the photo-peak efficiency of the semiconductor High Purity Germanium (HPGe) detector system are suggested and…
The MAJORANA Collaboration is searching for the neutrinoless double-beta decay of the nucleus $^{76}$Ge. The MAJORANA DEMONSTRATOR is an array of germanium detectors deployed with the aim of implementing background reduction techniques…
In this article, we discuss two specific classes of models - Gaussian Mixture Copula models and Mixture of Factor Analyzers - and the advantages of doing inference with gradient descent using automatic differentiation. Gaussian mixture…
Next-generation wireless systems such as 6G operate at higher frequency bands, making signal propagation highly sensitive to environmental factors such as buildings and vege- tation. Accurate Radio Environment Map (REM) estimation is…
We develop an optimal Bayesian solution for jointly inferring secondary signals in the Cosmic Microwave Background (CMB) originating from gravitational lensing and from patchy screening during the epoch of reionization. This method is able…
We propose a highly data-efficient active learning framework for image classification. Our novel framework combines: (1) unsupervised representation learning of a Convolutional Neural Network and (2) the Gaussian Process (GP) method, in…
Graph generation is a crucial task in many fields, including network science and bioinformatics, as it enables the creation of synthetic graphs that mimic the properties of real-world networks for various applications. Graph Generative…
We describe a physics simulation software framework, MAGE, that is based on the GEANT4 simulation toolkit. MAGE is used to simulate the response of ultra-low radioactive background radiation detectors to ionizing radiation, specifically the…
We present the use of a low background counting facility, equipped with a p-type 80% relative efficiency HPGe detector, protected by active and passive shielding, and large enough to count a 10" photo-multiplier tube (PMT). A GEANT4…
This paper investigates a channel estimator based on Gaussian mixture models (GMMs) in the context of linear inverse problems with additive Gaussian noise. We fit a GMM to given channel samples to obtain an analytic probability density…
$\mathrm{\gamma}$-ray spectroscopy is a quantitative, non-destructive technique that may be utilized for the identification and quantitative isotopic estimation of radionuclides. Traditional methods of isotopic determination have various…
We propose and demonstrate that a gamma-gamma collider with W_gg < 12 GeV can be added to the European XFEL with a minimal disruption to its main program. High-energy photons will be obtained by Compton scattering of 0.5 micron laser…
Recently, there appears lots of papers on the possibility of light Dark Matter (DM) in MeV and sub-GeV scale. Until now, only INTEGRAL and COMPTEL provided experimental data of 511keV of galactic center, and two spectra of Galactic Diffuse…
Gas Electron Multiplier (GEM) detector, one of the advanced members of the Micro Pattern Gas Detector (MPGD) group, is widely used in High Energy Physics (HEP) experiments. The high rate handling capability and spatial resolution make it a…
Early detection of lung cancer is critical for improvement of patient survival. To address the clinical need for efficacious treatments, genetically engineered mouse models (GEMM) have become integral in identifying and evaluating the…
We introduce a novel approach to improve unsupervised hashing. Specifically, we propose a very efficient embedding method: Gaussian Mixture Model embedding (Gemb). The proposed method, using Gaussian Mixture Model, embeds feature vector…