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Anomaly detection is a crucial task in machine learning that involves identifying unusual patterns or events in data. It has numerous applications in various domains such as finance, healthcare, and cybersecurity. With the advent of quantum…

Quantum Physics · Physics 2023-11-07 Julien Mellaerts

The distribution of a neural network's latent representations has been successfully used to detect out-of-distribution (OOD) data. This work investigates whether this distribution moreover correlates with a model's epistemic uncertainty,…

Machine Learning · Computer Science 2021-02-24 Janis Postels , Hermann Blum , Yannick Strümpler , Cesar Cadena , Roland Siegwart , Luc Van Gool , Federico Tombari

In this work we investigate the impact of two phenomenological Beyond the Standard Model (BSM) scenarios concerning the role of neutrinos in the early universe: non-standard neutrino interactions (NSI) and non-unitary three-neutrino mixing.…

High Energy Physics - Phenomenology · Physics 2025-10-13 Gabriela Barenboim , Stefano Gariazzo , Alberto Sánchez-Vargas

In this work, we examine the possibility of realizing a strongly first-order electroweak phase transition within the minimal classically scale invariant extension of the standard model (SM), previously proposed and analyzed as a potential…

High Energy Physics - Phenomenology · Physics 2014-10-22 Arsham Farzinnia , Jing Ren

Active learning has long been a topic of study in machine learning. However, as increasingly complex and opaque models have become standard practice, the process of active learning, too, has become more opaque. There has been little…

Machine Learning · Statistics 2018-06-26 Richard L. Phillips , Kyu Hyun Chang , Sorelle A. Friedler

The continued interest in placing bounds on the neutron's Electric Dipole Moment (EDM) is due to the implications regarding the characteristics of the strong interaction and, in particular, its behavior under the CP symmetry. In this work,…

High Energy Physics - Phenomenology · Physics 2024-11-26 Octavio Guerrero , Libertad Barrón-Palos , Daniel Sudarsky

We examine the electroweak breaking mechanism in the minimal supersymmetric standard model (MSSM) using the {\em complete} one-loop effective potential $V_1$. First, we study what is the region of the whole MSSM parameter space (i.e.…

High Energy Physics - Phenomenology · Physics 2008-11-26 B. de Carlos , J. A. Casas

Efficiently creating a concise but comprehensive data set for training machine-learned interatomic potentials (MLIPs) is an under-explored problem. Active learning, which uses biased or unbiased molecular dynamics (MD) to generate candidate…

The measurements of the muon and electron anomalous magnetic moments hint at physics beyond the standard model. We show why and how models inspired by asymptotic safety can explain deviations from standard model predictions naturally. Our…

High Energy Physics - Phenomenology · Physics 2020-10-21 Gudrun Hiller , Clara Hormigos-Feliu , Daniel F. Litim , Tom Steudtner

The scale of neutrino masses and the Planck scale are separated by more than twenty-seven order of magnitudes. However, they can be linked by imposing the stability of the electroweak (EW) vacuum. The crucial ingredient is provided by the…

High Energy Physics - Phenomenology · Physics 2015-06-18 Luigi Delle Rose , Carlo Marzo , Alfredo Urbano

The Standard Model of electroweak interactions is shown to include a gauge theory for the observed scalar and pseudoscalar mesons. This is done by exploiting the consequences of embedding the SU(2)left X U(1) group into the chiral group of…

High Energy Physics - Phenomenology · Physics 2009-10-28 B. Machet

We construct models in which electroweak symmetry is spontaneously broken by supersymmetric strong dynamics at the TeV scale. The order parameter is a composite of scalars, and the longitudinal components of the W and Z are strongly-coupled…

High Energy Physics - Phenomenology · Physics 2019-08-17 Markus A. Luty , John Terning , Aaron K. Grant

The Standard Model prediction for $\epsilon'/\epsilon$ based on recent lattice QCD results exhibits a tension with the experimental data. We solve this tension through $W_R^+$ gauge boson exchange in the $SU(2)_L\times SU(2)_R\times…

High Energy Physics - Phenomenology · Physics 2018-06-13 Naoyuki Haba , Hiroyuki Umeeda , Toshifumi Yamada

In this work, we examine the effectiveness of an uncertainty quantification framework known as Evidential Deep Learning applied in the context of biomedical image segmentation. This class of models involves assigning Dirichlet distributions…

Image and Video Processing · Electrical Eng. & Systems 2025-04-24 Hai Siong Tan , Kuancheng Wang , Rafe Mcbeth

In this paper, we attack the anomaly detection problem by directly modeling the data distribution with deep architectures. We propose deep structured energy based models (DSEBMs), where the energy function is the output of a deterministic…

Machine Learning · Computer Science 2016-06-17 Shuangfei Zhai , Yu Cheng , Weining Lu , Zhongfei Zhang

The mechanism of the electroweak symmetry-breaking (EWSB) is studied in the context of the heavy top quark, whose large mass may provide a clue as to the mechanism which generates the mass of the $W^\pm$ and $Z$ bosons. As a result, it…

High Energy Physics - Phenomenology · Physics 2007-05-23 Tim M. P. Tait

The increasingly precise neutrino experiments raise the hope for searching for new physics through studying the impact of Neutral Current (NC) Non-Standard Interactions (NSI) of neutrinos with matter fields. Neutrino oscillation experiments…

High Energy Physics - Phenomenology · Physics 2024-10-22 Saeed Abbaslu , Mehran Dehpour , Yasaman Farzan , Sahar Safari

Electroweak precision measurements can provide indirect information about the possible scale of supersymmetry already at the present level of accuracy. We update the present-day sensitivities of precision data using the new experimental…

High Energy Physics - Phenomenology · Physics 2009-11-11 J. Ellis , S. Heinemeyer , K. A. Olive , G. Weiglein

It has been argued that any primordial B+L asymmetry existing at very high temperatures can be subsequently erased by anomalous electroweak effects. We argue that this is not necessarily the case in the supersymmetric standard model…

High Energy Physics - Phenomenology · Physics 2010-11-01 Luis E. Ibanez , Fernando Quevedo

Machine learning interatomic potentials (MLIPs) enable accurate atomistic modelling, but reliable uncertainty quantification (UQ) remains elusive. In this study, we investigate two UQ strategies, ensemble learning and D-optimality, within…

Materials Science · Physics 2025-08-06 Fei Shuang , Zixiong Wei , Kai Liu , Wei Gao , Poulumi Dey
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